**2. Literature review**

Although fossil fuel complete our desire of electricity but on the other hand these are destructing the planet, so now day's renewable energy resources including hydroelectric, geothermal, solar thermal, biofuels, biomass, wave, tidal, and wind are being used to generate electrical power. More importantly, wind and solar are more developed due to their environment friendly characteristics [7]. There is uncertainty in the output of solar and wind or it can be said that their output is not constant, and depend on season whether it is sunny days or cloudy and also the location for proper required wind speed. This uncertainty in output of these renewable energy resources result in the requirement of energy storage devices for the reliability and improvement in economy of power system [8]. Major problem associated for renewable energy resources is the inconsistent power output, that can easily be reduced and solved using battery energy storage technology, along with that it result in decarburization of energy mix and mitigation of CO2 emission, and global warming effects. BESS can easily be adopted in off grid as well as in on grid system, also at any location in the power system from generation to consumer. Batteries installed at solar photovoltaic PV and wind power plant allow owners to store the energy when energy prices are low or there is inexpensive and uneconomic to supply to grid, and can be released to use during high prices time. Batteries installed with PV system and wind generator at household level increase self-produced and self-consumption electricity, a household PV system with battery system result in increment of selfconsumed energy about 30% without storage to 60–70%, along with that efficiency is increased and also additional power requirement from grid is decreased [9].

Now a day most of the storage in every country is the pumped hydro storage with the capacity of 200 MW, about 25 MW of electrical power is generated using pumped hydro storage plant, out of that 22 MW is being generated in United States. These plants are basically used during peak demand time, also providing water for the nuclear and steam power plant to enhance their performance efficiency and frequency control and regulation [10]. Another bulk storage technique in which air is compressed at the time of low demand with low energy prices, and during peak hour power can be generated at low cost with respect to stand alone gas turbines [11]. Because of new technology in concentrated solar thermal power system and photovoltaic system, demand of energy storage system is increasing in offshore platforms, and telecommunication installations (which are remote area power supply system), mobile applications, emergency backup, gird connected renewable power plants, and stressed electricity supply system [12].

This study shows the renewable energy generation and energy storage analysis in the Finland, It is committed that by year 2050 greenhouse effects will be reduced to 80–97% as compared to year 1990 [13]. Finland is dominating on run of river hydropower with limited capacity of 5.5Twh approximately, during months of December–April in winter season water is stored in reservoir and in summer season, that stored water is used to generate electrical power [14]. It is examined that

### *The Role of Energy Storage with Renewable Electricity Generation DOI: http://dx.doi.org/10.5772/intechopen.96114*

energy storage technologies can play an important role for getting proper benefit of solar resources, along with that gas storage, thermal energy storage, stationary batteries and power to gird technologies are also discussed [15]. Solar photovoltaic and wind are variable sources of power generation; about 70% of total energy generation is being generated using these technologies, about 51% of renewable energy generation is stored and 47% is directly utilized [16]. This study is about United states, inspite of knowing the benefits of energy storage technologies, only 2.5% of total electric power of United States is being stored (out of that most part is hydro pumped storage system), which is about 10% of Europe and 15% of Japan energy storage [17]. About 99% of worldwide storage capacity of 127000 MW is pumped storage, at second compressed air storage with capacity of 440 MW. Electrochemical energy storage has lot of system friendly characteristics i.e. high round trip efficiency, no any pollution, flexible energy and power characteristics, long life and low maintenance. Because of compact size of batteries, these are suitable for distributed locations, also can reduce variation in output voltage of solar PV and wing power plants [18]. From this study it is estimated to increase the renewable generation around 60–80% by the year 2030, which is currently about 20% of total generation of the country; at same time, high cost of battery and un availability of suitable location will result in the limited installment for compressed air energy storage and pumped hydro storage technologies [19].


*Article* **Analysis of Water Environment Quality Changes and Influencing Factors during the "Thirteenth Five-Year Plan" Period in Heilongjiang Province**

**Wei Chen 1,†, Yu Bai 2,†, Bo Li 1,\*, Chengcheng Feng 1,\* and Mi Zhou 3**

**Abstract:** Heilongjiang Province is located in the northeastern part of China and is the province with the highest latitude in China. As Heilongjiang Province is the most important grain production base in China, the Chinese government attaches great importance to the quality of the ecological environment in Heilongjiang Province, especially the analysis of changes in the quality of the water environment and their driving factors. We studied the changes in the environmental quality of surface water in Heilongjiang Province during the "13th Five-Year Plan" period (2016–2020), and analyzed the surface water for four major pollutants including the permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus, and the change trends of the proportion of the water quality of class I–III and the proportion of the water quality of inferior class V. The results show that the environmental quality of surface water in Heilongjiang Province has improved significantly during the "13th Five-Year Plan". The analysis of the driving factors of the change of surface water environment quality shows that the population, the primary industry, the tertiary industry and forestry are the main factors affecting the change of water environment quality in Heilongjiang Province.

**Keywords:** "Thirteenth Five-Year Plan" period; water environment quality; Heilongjiang Province; correlation analysis; surface water

#### **1. Introduction**

Located in northeastern China, Heilongjiang Province is the northernmost, easternmost and highest latitude province in China. Its north and east are separated from Russia across Heilongjiang River, its west is adjacent to the Inner Mongolia Autonomous Region, and its south is bordered by Jilin Province. With a total land area of 473,000 Km2, Heilongjiang Province is the sixth largest province in China. The geographical location and water system of Heilongjiang Province are shown in Figure 1.

The period from 2016 to 2020 was the time when China implemented the Outline of the Thirteenth Five-Year Plan for National Economic and Social Development of the People's Republic of China, hereinafter referred to as the "Thirteenth Five-Year Plan" period. During this period, the government of Heilongjiang Province focused on the improvement of the Songhua River Basin. All 44 black and odorous water bodies were treated, 72 industrial parks realized centralized sewage treatment, and 43 water source protection areas were all rectified for environmental problems. These results demonstrate the determination of Heilongjiang Province to improve the surface water environment.

**Citation:** Chen, W.; Bai, Y.; Li, B.; Feng, C.; Zhou, M. Analysis of Water Environment Quality Changes and Influencing Factors during the "Thirteenth Five-Year Plan" Period in Heilongjiang Province. *Water* **2022**, *14*, 2367. https://doi.org/10.3390/ w14152367

Academic Editors: Yaohuan Huang, Yesen Liu, Runhe Shi and Hongyan Ren

Received: 24 April 2022 Accepted: 16 July 2022 Published: 31 July 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**Figure 1.** Geographical location and water system of Heilongjiang Province.

At present, scholars' research on the surface water environment mainly focuses on the investigation and monitoring of new pollutants. For example, the research of Meng Qiao et al. (2022) showed that OPAHs exist preferentially in the water environment and pose a non-negligible ecological risk to the surface water ecosystem [1]. Hai-Yan Zou et al. (2021) studied the characteristics of antibiotic resistance genes (ARGs) in surface water affected by mining, and the results show that heavy metals from mining activities have significant effects on ARGs in surface water to varying degrees [2]. Nina Henning et al. (2021) detected GBP-Lactam, NA-GBP and CCHA at levels up to 260 ng/L in the Rhine River and its tributaries, suggesting monitoring of these compounds in drinking water [3]. Silvia Galafassi et al. (2019) reported on microplastic emissions, listing all identified sources of microplastic waste to date and a quantitative assessment of environmental inputs to surface water [4]. G. Sammut et al. (2017) conducted an extensive survey of perfluoroalkyl substances (PFAS) in surface waters of the Maltese Islands and the results show that all surface water samples are contaminated with at least one PFAS, with PFOS and PFOA detected in surface water at 100% and 95%, respectively [5].

In addition to increased monitoring of new pollutants, researchers have proposed a number of methods in recent years that may improve surface water monitoring. For example, Koyel Sur et al. (2021) conducted a pilot study in northwestern India, and he used green and shortwave-infrared (SWIR) bands to modify the Modified Normalized Difference Water Index (MNDWI) method, using this method to monitor the environmental quality of surface water [6]. The monitoring data can be processed and displayed using the Google Earth Engine (GEE) platform. Sama Azadi et al. (2021) conducted continuous monitoring of surface water around a new highway in southern Norway; he used the Gamma Test theory (GTT) method to optimize the water quality monitoring network (WQMN) of the road so that WQMN can be suitable for projects with limited design and construction time and budget or projects lacking sufficient data [7]. With the development of science and technology, there are more and more types of new pollutants, and their impact on the water environment is becoming more and more complex. Monitoring and research on new pollutants is often necessary. The development of science and technology will also lead to innovations in monitoring technology, and research on the testing and application scope of new technologies is also necessary to improve the level of environmental monitoring.

However, for a region as large as Heilongjiang Province, the introduction of new pollutants or new monitoring techniques into surface water monitoring should be carefully considered. This is because we are still at the stage of "little knowledge" about the sources of new pollutants and their impact on the ecological environment. At the same time, compared with the existing four major pollutants (permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus), the representation of new pollutants in water environmental quality monitoring is still low. In addition, the application of new measurement technology requires a lot of preliminary evaluation work to ensure the stability, practicability and data accuracy of the technology. The new approach needs also to be approved by other provinces in China. Therefore, it is still applicable to use four main pollutants (permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus) to characterize the overall water environment in Heilongjiang Province at this stage.

In recent years, research on the influencing factors of regional water environment quality has become an emerging topic at home and abroad. In terms of research methods, principal component analysis was used to analyze the water environment quality of the basin [8–11], and this method can be combined with other methods; the selection of influencing factors also enriches its research perspective. From the perspective of the scale of the study area, a small-scale study was also carried out, usually for a certain city. For example, Shexia Zhan et al. (2021) discussed the impact of natural factors and human activities on the source water quality in Macao based on the obtained statistical results [12]. The change of the regional water environment is a complex process affected by the comprehensive action of natural social and economic factors, and is the result of the interaction of the three systems of society, economy and ecology [13–15]. Factors such as climate, population, economy, transportation, energy consumption, water resources, agriculture and forestry are the main drivers of changes in the water environment. In the analysis of the correlation between water environmental quality and the three major systems, it tends to be large in scale, time and space, and the analysis direction changes from single target to multi-target, and develops from single factor to multi-factor, from static to dynamic, from the natural environment system to a complex natural and social environment system.

To sum up, many researchers have used different theories and methods to evaluate the regional water environment, making contributions to ecological and environmental protection, and the research results have a certain utility. However, most of the existing studies are limited to the influence of a certain factor on a single indicator or pollutant, and less attention is paid to the provincial perspective. Finally, there is a lack of analysis of the relationship between different water quality indicators and natural factors, socio-economic changes, etc., and a lack of tracking of driving factors. Therefore, this study attempts to answer the following research questions: (1) How will the water environment quality change in Heilongjiang Province during the 13th Five-Year Plan? Compared with the "Twelfth Five-Year Plan", is the water quality better or worse? (2) What factors drive the change of water environment quality in Heilongjiang Province? What factors dominate? Exploring the changes in water environment quality and its influencing factors in the development process of the "Thirteenth Five-Year Plan" is not only of great practical significance for realizing the high-quality development of Heilongjiang Province, but also has certain reference value for other developing countries.

#### **2. Materials and Methods**

#### *2.1. Study Area*

The water system in Heilongjiang Province is well developed. There are four major river systems in Heilongjiang Province, which belong to the four major river systems of Heilongjiang, Songhua River, Ussuri River and Suifen River. Among them, Heilongjiang and Ussuri River are the international boundary rivers, Xingkai Lake is the international boundary lake, Suifen River directly enters the Sea of Japan, and Songhua River and Nen River run through Heilongjiang Province. Heilongjiang Province has 2881 rivers with a drainage area of more than 50.0 Km2, 93 rivers between 1000 and 10,000 Km2, and 18 rivers with an area of more than 10,000 Km2. There are 253 lakes with an annual water surface area of 1.0 Km2 and above, including 241 freshwater lakes and 12 saltwater lakes, with a total water surface area of 3037.0 Km2 (excluding the overseas area of transboundary lakes). The main lakes are Xingkai Lake, Jingbo Lake and Lianhuan Lake.

#### *2.2. Research Methods and Data*

The grey relational analysis belongs to the grey system theory, and it further studies the degree of correlation between the indicators through the similarity of the changes in the geometric shapes of the indicators [16]. The basic idea is to use the quantitative analysis of the dynamic process to calculate the correlation degree between the reference index and each comparison index in the system, and to determine the important factors that affect the reference index. It can describe the degree of correlation between variables despite incomplete information. The larger the correlation coefficient is, the closer is the relationship between the reference index and the comparison index, helping analysis of the positive factors that are conducive to the development of the system. Grey relational analysis is not limited by sample size and distribution, and is also applicable to data with short time span and irregularity. Since there is much unknown information about the mechanism of the impact of other factors on the quality of the ecological environment, it conforms to the characteristics of the grey system.

According to the characteristics of the data, it was divided into seven categories: climate, population, economy, energy, water resources, forestry, and agriculture. Among them, for the climate index we selected the average temperature, the average annual precipitation and the annual sunshine hours; for the population index we selected the population of Heilongjiang Province; for the economic index we selected the per capita GDP, primary industry, secondary industry, tertiary industry and local environmental protection expenditure; for the energy index we selected the elastic coefficient of energy consumption; for the water resources index we selected the surface water resources, the total surface water supply, the total groundwater supply, the total agricultural water use, the total ecological water consumption and the per capita water consumption; for the forestry index we selected the area of artificial afforestation in the current year; for the agricultural index we selected the pure amount of agricultural nitrogen fertilizer application, the pure amount of agricultural phosphorus fertilizer application, the pure amount of agricultural potassium fertilizer application and the amount of pesticide use; for the water environment index we selected permanganate index, chemical oxygen demand, ammonia nitrogen, total phosphorus and excellent water body proportion. The calculation method of grey relational analysis was adopted, and the details can be seen in Junli Li et al. (2020) research [17]. The data comes from the 2016–2020 "Eco-environmental Quality Status of Heilongjiang Province" [18–22], "Heilongjiang Province Eco-Environmental Quality Status Bulletin" [23–27], "Heilongjiang Ecological Environment Statistical Annual Report" [28–30], "China Statistical Yearbook 2020" [31]. The flow chart is shown in Figure 2. We can obtain the reference sequence and the comparison sequence, respectively:

**Figure 2.** The flow chart of this study.

Reference sequence: statistics related to climate, population, economy, energy, water resources, forestry and agriculture in Heilongjiang Province from 2006 to 2020.

Comparative sequence: the annual average values of permanganate index, chemical oxygen demand, ammonia nitrogen, total phosphorus and the proportion of excellent water bodies in Heilongjiang Province from 2006 to 2020.

In addition, in order to understand the impact of pollution discharge on water environment quality in Heilongjiang Province, the Spearman correlation analysis method was used to analyze the permanganate index, chemical oxygen demand, ammonia nitrogen

and industrial source chemical oxygen demand discharge, industrial sources of ammonia nitrogen emissions, domestic sources of chemical oxygen demand emissions and domestic sources of ammonia nitrogen emissions in Heilongjiang Province from 2006 to 2019. The pollution emission data comes from the "2019 China Ecological Environment Statistical Yearbook" [32].

#### **3. Results**

#### *3.1. Changes in the Environmental Quality of Surface Water during the "13th Five-Year Plan" Period*

The proportions of water quality categories and changes in major pollutants in three different water stages of rivers in Heilongjiang Province From 2011 to 2020 can be seen in Tables 1 and 2. Among them, during the "13th Five-Year Plan" period, the proportion of water quality of class I–III in the dry season is 52.0–74.0%, the proportion of water quality in class I–III in the normal water period is 62.6–69.2%, and the proportion of water quality in class I–III in the high water period is 26.4–64.5%. From 2016 to 2020, the change of the proportion of water quality of class I–III in each water period is in a trend of fluctuation, but from 2011 to 2020, except for the wet season, the change trend of the proportion of water quality of class I–III in other water periods is a significant increase. During the "Thirteenth Five-Year Plan" period, the proportion of water quality of inferior Class V in the dry season is 3.9–9.2%, the proportion of water quality of inferior Class V in the normal water season is 2.8–7.4%, and the proportion of water quality of inferior Class V in the wet season is 0.9–5.8%. From 2016 to 2020, the change trend of the dry season and the flat water season is a fluctuating one, and the proportion of water quality of inferior Class V in the wet season has dropped significantly. The proportion of water quality of inferior Class V during the dry season from 2011 to 2020 fluctuates, and the proportion of water quality of inferior Class V during the normal and wet seasons decreases significantly. The above results show that although the water quality in the dry, flat and wet periods does not improve significantly during the "13th Five-Year Plan" period, the number of water bodies with poor water quality in the wet period is significantly reduced. Compared with the "Twelfth Five-Year Plan" period (2011–2015), during the "Thirteenth Five-Year Plan" period, the water quality in the dry and flat water periods is significantly improved, and the number of water bodies with poor water quality in the flat and wet periods is significantly reduced.

**Table 1.** 2011–2020 Proportion and change trend of water quality grades I–III in different water stages of rivers in Heilongjiang Province.

**Table 2.** The proportion and trend of water quality of inferior Class V in each water stage of Heilongjiang Province from 2011 to 2020.

The trend of major pollutants in rivers in Heilongjiang Province from 2011 to 2020 is shown in Table 3. During the "Thirteenth Five-Year Plan" period, the four major pollutants in Heilongjiang Province show a fluctuating trend. Compared with the end of the "Twelfth Five-Year Plan" (2015), the main pollution indicators of rivers in Heilongjiang Province, the permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus pollution concentration decrease by 16.7%, 18.2%, 34.7% and 33.3% respectively, and the permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus show a significant downward trend from 2011 to 2020. The above results show that the downward trend of the concentration of major pollutants during the "13th Five-Year Plan" period is not obvious, but compared with the "12th Five-Year Plan" period, the concentration of major pollutants has dropped significantly.

**Table 3.** The major pollutants in rivers of Heilongjiang Province from 2011 to 2020.

*3.2. Correlation Analysis between Pollution Discharge and Surface Water Environmental Quality*

The Spearman correlation coefficient was used to indicate the strength of the correlation between pollution discharge and major pollutants in the surface water environment, as shown in Figure 3. Among them, X1: surface water permanganate index, X2: surface water chemical oxygen demand, X3: surface water ammonia nitrogen, X4: industrial source chemical oxygen demand discharge, X5: industrial source ammonia nitrogen discharge, X6: living source chemical oxygen demand emissions, X7: ammonia nitrogen emissions from living sources. The results show that surface water permanganate index, chemical oxygen demand, ammonia nitrogen and industrial source chemical oxygen demand, ammonia nitrogen emission, living source chemical oxygen demand and ammonia nitrogen emission are all positively correlated. Among them, the permanganate index has a significant positive correlation with the chemical oxygen demand of industrial sources, chemical oxygen demand of living sources and ammonia nitrogen emissions from living sources, and has a very significant positive correlation with ammonia nitrogen emissions from industrial sources. The chemical oxygen demand of surface water has a very significant positive correlation with industrial source chemical oxygen demand, ammonia nitrogen, and living source chemical oxygen demand and ammonia nitrogen. There was a significant positive correlation between surface water ammonia nitrogen and chemical oxygen demand of industrial sources and ammonia nitrogen emissions from domestic sources.

**Figure 3.** Spearman correlation coefficients between pollutant emissions and major pollutants in surface water.

#### *3.3. Correlation Analysis between Surface Water Environmental Quality and Other Factors*

The grey correlation degree and its ranking of the surface water environmental quality comparison series are shown in Table S2 (Supporting Information). Specifically, the influencing factors with high correlation with the permanganate index are: the tertiary industry, the population of Heilongjiang Province, and net application amount of agricultural compound fertilizer. The influencing factors with a high degree of correlation with chemical oxygen demand are: tertiary industry, the area of artificial afforestation in the current year and the annual sunshine hours. The influencing factors with a high degree of correlation with ammonia nitrogen are: total surface water supply, pure amount of agricultural nitrogen fertilizer application, and per capita water consumption. The influencing factors with high correlation with total phosphorus are: total surface water supply, pure nitrogen fertilizer application and per capita water consumption. The influencing factors with high correlation with the proportion of excellent water quality are: primary industry, annual sunshine hours and tertiary industry.

In order to comprehensively evaluate the correlation between surface water environmental quality and various factors, the average method was used to evaluate the correlation index. There are 3 factors in the category of high correlation degree, which are population, forestry and agriculture in descending order of average degree of correlation, and 3 factors in the category of medium correlation degree, which are economy, meteorology and water resources in descending order of average degree of correlation. The factor in the category of low correlation degree is energy. The correlation statistics of each reference sequence are shown in Figure 4, and the average value is shown in Figure 5.

**Figure 4.** Statistical map of the correlation between each reference sequence and the environmental quality of surface water.

**Figure 5.** The average value of the correlation between each reference series and the environmental quality of surface water.

#### **High correlation factor**

The average grey correlation between population factors and water environment quality in Heilongjiang Province is 0.872, ranking first among the seven categories of factors, showing a very high correlation. Among the seven categories of factors, population has the greatest impact on water quality. The average grey correlation between forestry factors and water environment quality in Heilongjiang Province is 0.853, ranking second among the seven categories of factors, showing a very high correlation. The average grey correlation between agricultural factors and water environment quality in Heilongjiang Province is 0.834, ranking third among the seven categories of factors, showing a very high correlation.

#### **Medium correlation factor**

The average grey correlation degree between economic factors and water environment quality is 0.799, and the correlation degree is moderate. Among them, the primary industry, the tertiary industry, the per capita GDP, the secondary industry and the water environment quality are highly correlated, and the local financial environmental protection expenditure is low. The average grey correlation degree between climatic factors and water environment quality is 0.778, and the correlation degree is moderate. Among the climatic factors, the correlation degree of annual sunshine hours is greater than average temperature and precipitation, which is similar to ambient air quality. The average grey correlation degree between water resource factors and water environment quality is 0.748, and the correlation degree is medium. The average grey correlation degree of each factor in the water resources factor and the water environment quality is in descending order: total surface water supply, per capita water consumption, total agricultural water consumption, total groundwater water supply, surface water resources and total ecological water consumption quantity. Among them, the total surface water supply, per capita water consumption, total agricultural water supply and total groundwater supply are highly correlated with the environmental quality of surface water, while surface water resources and total ecological water are poorly correlated.

#### **Low correlation factor**

The average grey correlation between energy factors and water environment quality is 0.677, which is low. Among them, the energy consumption elasticity coefficient has a low correlation with the permanganate index, chemical oxygen demand, ammonia nitrogen, total phosphorus and the proportion of good water quality.

#### **4. Discussion**

During the "Thirteenth Five-Year Plan" period, the proportion of water quality of Class I–III increased, and the proportion of water quality of inferior Class V and the concentration of major pollutants decreased, indicating that the Heilongjiang Provincial Government's continuous "clear water defense war" has achieved remarkable results, mainly including continuous encryption monitoring and special inspection of law enforcement to ensure that inferior water bodies such as Ash River, Waken River, and Indus River do not rebound. In addition, through inter-departmental linkages to carry out special actions and crossmonitoring of water quality, the treatment of 44 black and odorous water bodies has been completed [33].

The primary industry has the greatest impact on the proportion of good water quality, and the primary industry refers to farmers and agriculture, forestry, animal husbandry, fishery, etc. As a major agricultural province, Heilongjiang Province has four major water systems flowing through a large amount of farmland. The surface water near the farmland is greatly affected by agricultural activities, resulting in the pollution of downstream waters [34]. This is consistent with the research results that the application rate of agricultural chemical fertilizers has a great influence on the content of ammonia nitrogen and total phosphorus in surface water. Heilongjiang Province is located in the highest latitude area in China, with four distinct seasons of precipitation, and the precipitation in the wet season is much higher than that in other water seasons. Fluctuations in water quality of Class I–III during the wet season and industrial wastewater discharge have little effect on ammonia nitrogen concentration in surface water; domestic wastewater discharge and primary industry have a greater impact on surface water ammonia nitrogen concentration. These results show that the effluent from farmland water pollution caused by surface water runoff and pollution caused by domestic wastewater discharge are the main sources of ammonia nitrogen and total phosphorus pollution in surface water in Heilongjiang Province. Therefore, the surface water pollution caused by living sources and agricultural sources

should be listed as the key work of the future surface water environment management in Heilongjiang Province [35].

The tertiary industry has a greater impact on the permanganate index, chemical oxygen demand and the ratio of good water quality. China's tertiary industry is other than the primary and secondary industries, and includes water conservancy, environment and public facilities management, etc. [36]. Due to the increasing investment in environmental protection in Heilongjiang Province, this may be related to the increase in the number of sewage treatment plants [28–30], which means that the increase in sewage treatment capacity indirectly affects the quality of surface water in Heilongjiang Province [37]. This is consistent with the research results that local financial environmental protection expenditures have low correlations with permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus, but are correlated with the proportion of good water quality. It shows that although the local financial environmental protection expenditure has little effect on the content of pollutants in surface water, it can affect the comprehensive situation of surface water quality in Heilongjiang Province.

Forestry factors are highly correlated with the environmental quality of surface water in Heilongjiang Province. The regulatory effect of forests on surface water is mainly due to the good water storage function and hydrological effect of the forest litter layer and soil layer. These effects will promote the improvement of water environment quality. Although there are certain differences between different forest lands, the regulatory effect of natural mixed forest is better than that of pure forest or artificial afforestation.

As further studies on the impact of land use patterns on surface water systems in recent years suggest that the contribution of forest drainage to surface water eutrophication may be greater than previously estimated [38,39], changes in forest surface runoff and the exposure of understory organic and inorganic layers can affect the concentrations of phosphorus, nitrogen, and dissolved organic carbon in surface waters [40]. The study by Lepistö et al. (2021) shows that the percentage of forest drainage is positively correlated with the total organic nitrogen in forest streams, which in turn is correlated with the total organic carbon concentration [41]. This shows that the impact of forests on the environmental quality of surface water is not only positive, but may have some negative effects, especially on chemical oxygen demand, which is consistent with our findings. In addition, some natural factors such as annual sunshine hours and total surface water supply also have a major impact on the surface water environment, which shows that in addition to human activities, the role of natural conditions cannot be ignored.

#### **5. Conclusions**

During the "Thirteenth Five-Year Plan" period, the annual average concentration of major pollutants in surface water in Heilongjiang Province has dropped significantly, the proportion of water quality of Class I–III has increased, the proportion of water quality inferior to Class V has decreased, and the overall environmental quality of surface water has improved. Research on the driving factors of water quality change shows that nitrogen and phosphorus pollutants in farmland surface water runoff and domestic sewage are the main sources leading to ammonia nitrogen and total phosphorus pollution in surface water in Heilongjiang Province. The increase of sewage treatment plants has a greater impact on the permanganate index, chemical oxygen demand and the proportion of good water quality, which indirectly affects the overall water quality of Heilongjiang Province. It is worth noting that the impact of forests on the environmental quality of surface water in Heilongjiang Province is complex and may lead to increased chemical oxygen demand in surface water. In addition, the influence of natural factors on the surface water environment, such as the total annual water supply and surface water supply in Rizhao City cannot be ignored.

**Supplementary Materials:** The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/w14152367/s1, Table S1: Basic items of surface water environmental quality※ Standard limit. Table S2: Grey correlation degree and ranking of surface water environmental quality comparison series.

**Author Contributions:** Conceptualization, B.L. and W.C.; methodology, C.F.; software, C.F.; resources, W.C.; writing—original draft preparation, C.F.; writing—review and editing, Y.B. and M.Z.; visualization, C.F.; supervision, Y.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Acknowledgments:** We would like to thank the Heilongjiang Provincial Department of Ecology and Environment for providing data support for this study, and Fengying Zhang from China Environmental Monitoring Station for providing technical guidance for this paper.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **Long-Term Study of Monitoring History and Change Trends in Surface Water Quality in China**

**Fengying Zhang 1,2,†, Lanyu Lin 1,†, Wenpan Li 1, Dekun Fang 1, Zhuo Lv 1, Mingsheng Li 1, Guangwen Ma 1, Yeyao Wang 1, Li Wang 3,\* and Lihuan He 1,\***

**Abstract:** To investigate the monitoring history and long-term change trends in surface water quality in China since the reform and opening up, the history of surface water environment monitoring is summarized, including monitoring scope, monitoring methods, and technical requirements. Temporal and spatial patterns of surface water quality in China were analyzed based on the monitoring results. In the past 40 years, the monitoring targets for surface water quality have been continuously improved, the frequency of monitoring has become more science-based, and the monitoring indicators are now comprehensive. Overall, the temporal change trend in surface water quality has followed a "fluctuating changes stage—rapid deterioration stage—fluctuations stalemate stage rapid improvement stage" pattern. However, the current regional surface water quality is still in a polluted status, and there is a gap between surface water quality status and the goal of building a well-off society. At present, China's surface water pollution is prone to high numbers of incidents and the treatment of surface water pollution has entered a crucial stage. The potential for the continuous reduction of major pollutant discharges has become more challenging, and the marginal cost for pollution control has increased. It is very difficult to comprehensively solve the outstanding water environment problems. In addition to strengthening the existing work on surface water quality control, it is also necessary to strengthen the work of risk identification, early warning, and regulation implementation of the surface water environment. During the 14th year plan period (2021–2025), the overall planning on water resources, water ecology, and water quality will be implemented, and beautiful rivers and lakes will be created.

**Keywords:** surface water; monitoring history; change trends in surface water quality; water quality protection

#### **1. Introduction**

Environmental monitoring is an important cornerstone of environmental protection and an important support for the construction of an ecological civilization and beautiful China [1–3]. Water quality monitoring is an important branch of environmental monitoring [2], which refers to the process of sampling and measuring various characteristic indexes of water to grasp the water environment quality status and the dynamic changes of pollutants in the water system, as well as to record the process [2]. Monitoring is the basis for water pollution control, environmental management, and scientific research. Through water quality monitoring, we can master the dynamic changes in the water environment and provide first-hand scientific data to support decisions regarding the prevention and

**Citation:** Zhang, F.; Lin, L.; Li, W.; Fang, D.; Lv, Z.; Li, M.; Ma, G.; Wang, Y.; Wang, L.; He, L. Long-Term Study of Monitoring History and Change Trends in Surface Water Quality in China. *Water* **2022**, *14*, 2134. https:// doi.org/10.3390/w14132134

Academic Editors: George Arhonditsis and Danny D. Reible

Received: 21 April 2022 Accepted: 28 June 2022 Published: 4 July 2022

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control of water pollution and the formulation of environmental protection policies and environmental legislation [2,4].

Many scholars have conducted a great deal of water quality research in China [5–7], but most studies conducted to date have focused on one aspect [8,9] or on a single river basin or lake [10–13]. Studies focused on long-term sequences across the country are rare [12]. The 40th anniversary of China's reform and opening up was in 2018; accordingly, it is important to summarize the history of water quality monitoring and water environmental protection during the past 40 years, as well as to analyze the trends in surface water quality during this time, which could provide support for precise pollution control and environmental management [11,12].

In this study, the history of surface water quality monitoring and surface water environmental protection is summarized, temporal and spatial variations in surface water quality are analyzed, and the current existing problems and pressure on surface water quality are proposed. The analyses conducted in this study are based on the Eco-Environmental Quality Report of China from 1980 to 2020 [14], the Report on the State of the Eco-environment in China from 1989 to 2020 [15], and other eco-environmental quality reports, related policy norms, and data from the government, combined with water quality monitoring data. The results presented herein will provide a foundation and scientific research support that will facilitate pollution prevention and control and enable the realization of an ecologically friendly civilization in China.

#### **2. Materials and Methods**

Due to the availability and integrity of historical monitoring data, our study area focuses on mainland China. All data used in this study were derived from environmental reports, statistical year books, government reports, relevant literature, or professional websites. Environmental reports included the China Eco-Environmental Quality Report (1980–2020) [14], Report on the State of Ecology and the Environment (1989–2020) [15], and the Annual Statistics Report on the Environment in China (1998–2015) [16]. Statistical yearbooks and government reports investigated included the China Statistical Yearbook [17], China Environmental Yearbook [18], government work reports, etc. Relevant literature and professional websites, such as academic literature from the China National Knowledge Internet (CNKI), Elsevier, and relevant data, policies, specifications, and systems published on governmental networks by the Ministry of Ecology and Environment (MEE), China National Environmental Monitoring Center (CNEMC), and the provincial-/city-level Ecology Environment Agency were also investigated.

The spatial distribution of surface water quality monitoring sites and surface water quality were evaluated by ArcGIS 10.0 with a license from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, and temporal patterns in water quality and pollutants were summarized by Origin 2018.

#### **3. Results and Discussion**

#### *3.1. History of Surface Water Quality Monitoring*

Surface water quality monitoring in China began in the 1980s. Although this was much later than developed countries, there has been considerable progress in the past 40 years. Currently, China's water environment monitoring technology covers large rivers, lakes, and other areas such as reservoirs, etc. Moreover, the monitoring techniques and means have been improved year by year.

China's water quality monitoring is conducted in a radiation mode. Specifically, the water quality monitoring center is the core, and the monitoring points are used as nodes to form the national surface water quality monitoring network, forming an integrated monitoring network covering the national-, provincial-, municipal-, and county-level surface water quality monitoring, and can meet the needs of water quality monitoring in different areas and different regions. At the same time, a combination of fixed-point sampling and mobile sampling is adopted to ensure the real-time accuracy of monitoring data.

#### 3.1.1. Monitoring Scope

In 1988, the former National Environmental Protection Agency (NEPA) first established a national surface water quality monitoring network consisting of 353 sections. In 1993, the NEPA re-examined and certified the monitoring sections in the national control monitoring network and confirmed that the national surface water quality monitoring network consisted of 313 national control sections [14,15].

In 2003, the NEPA further adjusted the national environmental monitoring network and monitoring sections and identified the national surface water quality monitoring network, which includes the Yangtze River, Yellow River, Haihe River, Liaohe River, Songhua River, Pearl River, and Huaihe River, the "Three Lakes" (Taihu Lake, Dianchi Lake, and Chaohu Lake), and the three regional rivers (rivers in Zhejiang and Fujian Province, rivers in northwestern China, and rivers in southwestern China). Overall, the monitoring network has 759 monitoring sections (604 rivers and 155 lakes) covering 320 rivers and 28 lakes [14,15].

In 2012, the NEPA released a new national environmental monitoring basin network consisting of 972 monitoring sections covering 420 rivers and 62 lakes. Water monitoring sections were set in the main stream of China's main water systems, the primary and secondary tributaries with an annual runoff of more than 500 million cubic meters, national border rivers and provincial rivers with an annual runoff of more than 300 million cubic meters, and large water conservancy facilities [14,15].

In July of 2015, the State Council issued the "Eco-Environmental Monitoring Network Construction Plan," which clearly defined the national surface water monitoring network during the "13th Five-Year Plan". The number of national control sections was increased from 972 in the "12th Five-Year Plan" to 1589 in 2015, including 1246 sections in 1366 rivers and 343 sections in 139 lakes. These sections (Figure 1) include 1940 assessment and ranking sections, 195 control sections for evaluation in the estuaries (of which, 85 are evaluation, assessment, and ranking sections), and 717 sections for scientific research. The "13th Five-Year" National Surface Water Quality Monitoring Network covers both the main rivers of the country and important primary and secondary tributaries, as well as the third and fourth tributaries of the key areas, key lakes/reservoirs, etc. Therefore, it has good regional spatial representation and can comprehensively, accurately, and objectively reflect the water quality and temporal–spatial distribution characteristics of pollutants in the water system or region [14,15].

In summary, China's national surface water quality monitoring is an organic whole based on monitoring of surface water quality, adherence to water and land planning, land and sea planning, river and lake planning, upper and lower planning, urban and rural planning, and comprehensive monitoring of the national aquatic environment ecosystem.

**Figure 1.** China national surface water quality monitoring network in 2020.

#### 3.1.2. Monitoring Indicators

The monitoring indicators during the past 40 years were listed in Appendix A. Before 2011, there were 11 monthly monitoring indicators pertaining to water quality in rivers (water temperature, pH, conductivity, dissolved oxygen, permanganate index, five-day biochemical oxygen demand, ammonia nitrogen, petroleum, volatile phenols, mercury, and lead). When monitoring the water quality in lakes and reservoirs, total phosphorus, total nitrogen, chlorophyll a, transparency, and water level were also included [14,15].

After the Measures for the Evaluation of Surface Water Quality was issued in 2011, the monthly monitoring was conducted in accordance with the 24 indicators, as shown in the Surface Water Quality Standards (GB3838-2002) [14,15] (Appendix B).

#### 3.1.3. Monitoring Frequency

The monitoring frequency of surface water quality has increased obviously [14,15]. Before 2003, the monitoring frequency of surface water quality was generally low (about six times per year), and it was monitored according to the water periods, including dryness, flatness, and abundance.

Monthly monitoring has been conducted since the establishment of the monthly reporting mechanism based on the national water quality monitoring system in 2003. Monitoring is conducted for the first 10 days of the month.

Since October 2017, the sampling and laboratory analysis separation mode has been fully implemented, the monitoring frequency has been increased, and the monitoring work now is being conducted quarterly, monthly, weekly, daily, and, even, one time per four hours.

#### 3.1.4. Monitoring Method

Sampling for surface water quality monitoring is mainly conducted manually. Since the beginning of the 21st Century, the state has built 150 automatic surface water quality monitoring stations in the provincial boundary sections of major rivers and important border rivers to provide early warnings regarding water quality. From July 1st 2009, realtime water quality data from national water quality automatic monitoring stations have been released to the public and published online [14,15].

Since October 2017, the 1940 national surface water assessment sections have fully implemented the sampling and laboratory analysis separation mode. By the end of July 2018, 2050 automatic surface water quality monitoring stations were built. Future water quality monitoring will be based on automatic monitoring supplemented by manual monitoring, leading to comprehensive realization of sampling and laboratory analysis separation, automatic monitoring, and data sharing [14,15].

#### 3.1.5. Surface Water Quality Standard

Over the past 40 years, China's surface water environmental quality standards have undergone four major changes [19]. In 1983, the Environmental Quality Standard for Surface Water (GB 3838-83) was promulgated and implemented for the first time. In 1988, the Environmental Quality Standard for Surface Water was revised to the Environmental Quality Standard for Surface Water (GB 3838-88). In 1999, this was revised to the Environmental Quality Standard for Surface Water (GHZB 1-1999) and, in 2002 to the Environmental Quality Standard for Surface Water (GB 3838-2002) [14,15].

#### *3.2. Spatial Temporal Trends in Surface Water Quality*

#### 3.2.1. General Temporal Change Trends

Figure 2 showed the general temporal change trends of surface water quality. In the past four decades, the national surface water quality has shown a trend of fluctuating changes–rapid deterioration–volatility–rapid improvement.

**Figure 2.** Annual ratio of water quality in China during 1978–2020.

The period of fluctuating changes was from 1978 to 1983. During this period, the annual ratios of grade I–III sections (sections with water quality between grade I and grade III) ranged from 20.0% to 30.5% and the annual proportions of inferior grade V sections (sections in which water quality failed to meet grade V) were from 28.0% to 36.3%. In this period, the overall situation of China's surface water quality transitioned from basically clean to partially deteriorating.

The stage of rapid deterioration was from 1984 to 1990. During this time, the annual ratio of grade I–III sections decreased by 18.7% from 45.6% in 1984 to 26.9% in 1990, while the proportion of inferior grade V sections increased by 12.8%, from 15.8% in 1984 to 28.6% in 1990. This stage corresponded to the beginning of reform and opening up, accompanied with fast economic and social development. The eastern part of China, including the Yangtze River Delta and the Pearl River Delta region, had begun to undergo rapid development, foreign enterprises gradually moved in, and local enterprises developed everywhere. The environmental effects caused by the rapid development of industry were

gradually emerging, especially in the 7th Five-Year Period (1986–1990), and pressure on the surface water quality in China began to increase. In this period, although the status and role of environmental protection in social and economic development were clarified, the relationship between economic construction and environmental protection had not been rationalized. As a result, the surface water quality generally evolved from partial deterioration to general deterioration.

The phase of volatility was from 1991 to 2001. During this period, the annual ratio of sections that met the water quality standard (water quality in grade I to grade III, grades I–III for short) was from 25.7% to 34.5%, and the proportion of inferior grade V sections was from 32.4% to 35.7%.

The rapid improvement period was from 2002 to 2020, during which time, the annual ratio of grade I–III sections increased by 48.8%, from 34.6% in 2002 to 83.4% in 2020, while the proportion of inferior grade V sections decreased by 34.3% from 34.9% in 2002 to 0.6% in 2020. During the "10th Five-Year Plan" period, water pollution in the country was initially curbed and environmental quality improved in some areas. These improvements were mainly attributable to the initial recognition of the relationship between economic development and the implementation of water environmental protection, strict industrial structure adjustment policies, urban sewage centralized treatment, total control, and key river basin water pollution prevention and control planning systems [20].

During the "11th Five-Year Plan" period, chemical oxygen demand and ammonia nitrogen were introduced as binding indicators in the environmental protection target, and the implementation of the environmental protection target responsibility system greatly improved the construction of pollution control facilities and promoted the improvement of the level of the conventional pollution indicators. During this period, the overall surface water quality of the national water environment was stable, and the water quality improved. The water quality of the main stream in the key river basin was obviously improved. The concentration of the main pollution indicators of the tributaries dropped drastically, and water pollution prevention and control work in the basin made remarkable achievement.

#### 3.2.2. Trends for Major Pollution Indicators

Among the major pollution indicators, the concentrations of permanganate and ammonia nitrogen showed similar temporal patterns (Figure 3), first increasing, then decreasing.

**Figure 3.** The annual concentration of NH3-N and CODMn during 1978–2020.

Among these, the annual ammonia nitrogen (NH3-N for short) concentration showed an increasing trend from 1978–1981, followed by a sharp decrease in 1982, then fluctuations in 1983 and 1986 and an obviously increasing trend during 1987 and 1995, which increased from the lowest value of 0.53 mg/L to the highest value of 2.00 mg/L. From 1996 to 2002, the annual concentration fluctuated from 0.93 mg/L to 2.36 mg/L, while it improved from 2003 to 2020, by a decrease in annual concentration from 2.62 mg/L to 0.22 mg/L.

The annual permanganate index (CODMn for short) concentration fluctuated from 1991 to 2002, with annual levels ranging from 5.5 mg/L to 9.2 mg/L, while the concentration improved from 2003 to 2020 when annual concentrations decreased from 9.6 mg/L to 3.2 mg/L.

#### 3.2.3. Spatial Temporal Changes in the Seven Major River Basins

In general, the water quality in the Yangtze River and Pearl River was good comparing with the rest of the basins. Haihe River had the worst water quality, and it was also the only water basin with grade V sections. The water quality rankings in 2020 were Yangtze River > Pearl River > Yellow River > Songhua River > Huaihe River > Liaohe River > Haihe River.

Figure 4 showed the changes of water quality in the major river basins during 2007–2020. During 2007 and 2020, the water quality in Yangtze River experienced an improvement–fluctuating changes–improvement pattern. The Yellow River, Pearl River. and Huaihe River have experienced improvement–deterioration–improvement changing patterns. The Songhua River, Haihe River and Liaohe River have showed fluctuating improvement. Since 2017, the water quality in the seven major river basins showed a rapid improvement, with an obvious increase for the ratio of grade I to III sections and a decreasing trend for the ratio of grade V sections.

**Figure 4.** Changes of water quality in the major river basins during 2007–2020.

#### *3.3. Surface Water Pollution Prevention and Control in China*

Analysis of the correlation between river environmental quality and pollutant emissions, national economic development level, and environmental pollution control investment revealed that the reduction of ammonia nitrogen and COD emissions [20] and the

increase in GDP and environmental pollution control investment are the main reasons for the improvements that have occurred in surface water quality [21,22].

China's surface water environmental protection work has been developed from scratch and expanded in scale [23]. During the past four decades, the intensity of surface water pollution control has increased, and the surface water ecological protection work has been strengthened, which has greatly improved the surface water environment in China [24].

Overall, in the past 40 years, China's environmental protection has experienced four development stages consisting of the initial "three wastes" governance, steady development of pollution prevention, a total quality control stage, and now, a new stage of environmental protection with improvement of environmental quality as the primary goal [25]. Since the founding of the country till the end of the 1970s, during the initial stage of development, China's surface water protection work has been in a disorderly status. The first national environmental protection work conference held in 1973 marked the beginning of water environment protection in China.

In the steady development stage from the 1980s to the early 21st Century, China's economy developed rapidly, while its water environmental protection work had achieved remarkable progress. During the "9th Five-Year Plan" period, the "Huaihe River Basin Water Pollution Prevention and Control Plan" was approved and implemented, marking China's entry into a stage of large-scale water pollution control. During this period, the country launched a comprehensive campaign targeting water pollution control of the Three Rivers and Three Lakes (Huaihe River, Haihe River, and Liaohe River and Taihu Lake, Dianchi Lake, and Chaohu Lake, respectively). Since then, organic matter pollution of surface water and the eutrophication of lakes have been effectively curbed, and the water environmental protection work has made significant progress. The total control led to a quality improvement from 2002 to 2014. In 2002, China issued the "Clean Production Promotion Law", which officially marked the transition from end-of-pipe treatment to total process control for China's water environment pollution control, and China's river environmental protection work entered a new stage.

In the same year, the MEP promulgated a new "Environmental Quality Standard for Surface Water" (GB3838-2002), among which the water quality evaluation indicator increased from 75 to 109, which was more in line with the status quo of surface water environmental protection in China. Since the "11th Five-Year Plan", target accountability for water quality control was introduced with more stringent and clear targets. The capacity of water quality control improved since then, and the water quality, in particular for the main stream in key river basins, improved significantly.

In the new stage of environmental protection with the improvement of environmental quality as the core (since 2015), the "13th Five-Year Plan" has entered a stage of double constraint on quality improvement and total control. This was marked by the 18th National Congress of the Communist Party of China (CPC). The ecological civilization's construction is included in the overall layout of the "five in one" plan, and water quality has become an important part of improving people's livelihood and building a well-off society. As a program of action for the prevention and control of water pollution in China, the "Water pollution prevention action plan" clarifies the quality improvement objectives of various water bodies in different periods, which was, by 2020, for the seven major river basins, the water quality with a good (grades I–III) ratio being above 70%, and by 2030, the ratio should reach 75%. The "13th Five-Year Plan for National Economic and Social Development Outline" also clarifies the dual-binding indicators for water quality improvement and total control, while the "13th Five-Year Plan for Ecological Environmental Protection" further proposes specific requirements for systematic treatment with quality improvement as the core.

The theory of harmonious coexistence between man and nature was introduced for development in China during the "13th Five-Year Plan", and the Yangtze River economic belt development and high-quality development and ecological protection for the Yellow River Basin were introduced. For the Yangtze River, the eco-environment restoration was put in a stronger position compared to development, and for the Yellow River, a comprehensive management of the eco-environment system, including the environment quality of mountains, rivers, forests, fields, lakes, and grasslands, and the pollution sources was planned, to promote high-quality development.

#### **4. Problems and Pressures**

Although water quality in China has improved significantly and an environmental turning point has begun to appear, water quality in some areas is still not improving. As a result, there is still a gap between the quality of the water environment and the goal of building a well-off society [7,10,26,27].

#### *4.1. Surface Water Is Still Polluted*

In 2020, the national surface water quality was fairly good. The main pollution indicators were chemical oxygen demand (COD), total phosphorus (TP), and the permanganate index, and the over-standard rates were 9.4%, 7.5%, and 5.8%, respectively. The proportion of the grade I–III section was 83.4%, which indicates that surface water quality in 16.6% of the sections was worse than grade III, while the proportion of sections that were worse than grade V was 0.6%. The Liaohe River and Haihe River were slightly polluted [14,15].

#### *4.2. Total Phosphorus Pollution Has Increased*

In 2020, the rate of sections with TP exceeding the national surface water standard was 7.5%, more than that of CODMn, and became the second over-standard indicator affecting the national surface water quality. The TP concentration in 20 lakes and one reservoir exceeded the standard; the TP pollution in the lake was higher than in the reservoir [14,15].

#### *4.3. High Pollutant Emission Intensity and Increasing Pollution from Residential Sources*

China's primary source of water pollution has changed from industrial pollution to domestic pollution, and there is now great pressure to reduce domestic sewage. With increased urbanization, the contribution of domestic pollution sources has become increasingly prominent, and it is now the main source of water pollution. As a result, pollution control of rural life at the township level needs to be strengthened. In 2015, the total discharge of wastewater was 73.53 billion tons in China, which was 2.7% greater than in 2014. However, industrial wastewater discharge was 19.95 billion tons, which was 2.8% lower than in the previous year, accounting for 27.1% of the total wastewater discharge. Domestic sewage discharge was 53.52 billion tons, which represented an increase of 4.9% over 2014 and accounted for 72.8% of the total wastewater discharge. Finally, the discharge of wastewater from centralized pollution control facilities was about 0.6 billion tons, accounting for 0.1% of the total wastewater discharge [14,15].

#### *4.4. The Problem of Lake Eutrophication Is Obvious*

In 2020, 76.8% of the 110 major lakes and reservoirs across the country met the grade I–III standard, while 15.2% and 2.7% met the grade IV and V standards, respectively, and 5.4% failed to meet the grade V standard. The main pollution indicators were TP, COD, and CODMn. Of the 110 lakes (reservoirs) being monitored for nutritional status, 10 were oligotrophic, 68 were mesotrophic, 26 were under slight eutrophication, six were under intermediate eutrophication, and one was under heavy eutrophication [14,15].

#### *4.5. Heavy Metal Levels in Surface Water Have Exceeded the Standard*

In 2019, there were 28 cases of heavy metals exceeding the standard in 23 surface water sections. The main indicators exceeding the standards were mercury, arsenic, and selenium. Among these, 12 cases exceeded the mercury limit, seven exceeded the arsenic limit, and three exceeded the selenium limit. From the perspective of the river basin, the over-standard sections were mainly distributed in the Yellow River, Haihe River, Yangtze River, and the Pearl River Basin, with 8 cases, 6 cases, 5 cases, and 4 case of heavy metals exceeding the standard, respectively. At the provincial level, the sections exceeding the standard are mainly distributed in Hebei, Inner Mongolia, Hubei, Hunan, Shanxi, and other areas.

#### **5. Conclusions**

In the past 40 years, China's environmental monitoring has made great progress. The monitoring of water quality is developing towards the continuous improvement of monitoring targets, the frequency of monitoring is becoming more reasonable, the monitoring indicators are being comprehensively covered, the technical methods are becoming scientific, and the quality standards are becoming increasingly stringent.

During this same period, the national surface water quality has shown a trend of fluctuating changes–rapid deterioration–volatility–rapid improvement. From 2002 to 2020, the water quality in the main watersheds was generally good, showing a gradual improvement trend, and the pollution was reduced. The main change has been that the proportion of water quality of grade I–III increased annually, while the proportion of inferior water quality of grade V has decreased. During 2002–2020, the proportion of grade I–III water sections increased from 34.6% to 83.4%, while the proportion of inferior grade V sections decreased from 34.9% to 0.6%. Furthermore, the water quality in the main river basins has improved.

The increase in GDP and environmental pollution control investment are the main reasons China's surface water environmental protection system has been developed from scratch and expanded, the intensity of surface water pollution control has been strengthened, and the surface water ecological protection work has increased, which has greatly improved the surface water environment in China.

However, with the current rapid development of the economy and high consumption of materials and energy, the number of surface water pollution incidents in China has been high, and the treatment of surface water environmental pollution has entered a crucial stage. Moreover, the potential for the continuous reduction of total pollutant discharges has been narrowing, while the marginal costs of governance are continually increasing. Accordingly, it has become very difficult to achieve comprehensive improvement of the water environment quality by focusing on solving the outstanding water environment problems in a short period of time. Therefore, it is necessary to improve risk identification, early warning systems, and regulation of surface water environments.

In the year 2022, the Chinese government released the "14th five-year plan for ecological environment protection", which enhances the regulations on water quality control. In this plan, specific measures are outlined for water quality monitoring, water ecology monitoring, and water pollution source monitoring. For water quality monitoring, a national water monitoring network will cover key basins and prefecture-level cities, supported mainly by automatic monitoring. The local water monitoring network should cover the major water bodies, major cities and towns, large industrial clusters, planting and breeding areas, and key boundaries. For water ecology monitoring, a water ecology monitoring framework should be established and implemented in the Yangtze River Basin. For water pollution source monitoring, the "water cross section-water quality-pollution source" monitoring traceability technology and three-dimensional monitoring network for surface sources should be established and forecast and warning capacity on water environment should be achieved.

**Author Contributions:** F.Z.: Conceptualization, Software, Formal analysis, Writing—Original Draft, Review & Editing, Supervision, L.L.: Conceptualization, Software, Formal analysis, Writing—Original Draft, W.L.: Resources, Data Curation, D.F.: Resources, Data Curation, Z.L.: Data Curation, Formal analysis, M.L.: Resources, Data Curation, Visualization, G.M.: Resources, Data Curation, Y.W.: Resources, Supervision, L.W.: Conceptualization, Writing—Review & Editing, Supervision, Funding acquisition, L.H.: Conceptualization, Writing—Review & Editing, Supervision. All authors have read and agreed to the published version of the manuscript.

**Funding:** The present study was funded by the Science and Technology Project of Beautiful China Ecological Civilization Construction (No. XDA23100400) and the National Natural Science Foundation of China (No. U2243206 and No. 42007414).

**Data Availability Statement:** All sources of data are cited throughout the paper.

**Acknowledgments:** The authors wish to thank all the staff members at the China National Environmental Monitoring Center for their strong support of this study.

**Conflicts of Interest:** All authors declare that they have no conflicts of interest to disclose in the context of this study.

**Appendix A. Monitoring Indicators during the Past 40 Years**

#### **References**

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*2.4. System Design*

In order to solve the above problems, this paper proposed an FD method based on CCA and JITL. We mainly used the CCA component to preprocess and normalize data, transform high-dimensional data into low-dimensional variable covariance subspaces and maximize the correlation between the most important top latent dimensions. SVD was applied to decompose the covariance matrix of input and output into two separate singular subspaces and keep the original distribution trends of variable correlations. Subspace mapping procedures projects input and output matrices back to the singular subspaces only with the most important relations and generates two groups of variables, Px and Py, after dimension reduction which eliminates the noise, that is, the residual subspaces. Then, JITL was used to calculate the Euclidean similarity of the query sample and the training data, respectively, and selected a sample subset for online testing regarding distances between them. During the experiments, the data sets of Px and Py were equally divided as a training data set and a testing data set. Finally, the FD model formulated statistics to define thresholds of fault signals and performed to detect signal faults in the testing samples. The workflows of the model are shown in Figure 2.

**Figure 2.** Flowchart of the proposed CCA-JITL FD model.


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2010. 264 p. doi:10.1007/978-0-387-46262-2

*Edited by Mohammad A. Matin*

The field of antenna engineering has been advancing at a remarkable pace to support modern communication systems. Recently, significant progress has been made in the development of new antennas and techniques targeted for applications in medical, defense, health care, communication, etc. The motivation of this project is to present cutting-edge research materials in the field of antennas for modern wireless communication.

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Modern Antenna Systems

Modern Antenna Systems

*Edited by Mohammad A. Matin*


**4.3 Numerical solution with various computational grids**

Deforming or moving finite element is used to consider the time delay in temperature at the outer wall of the slab [37]. Estimated values of wall heat flux and heat transfer coefficient are tabulated in **Table 3**. It can be observed from the table that the estimated wall quantities are having significant influence on the predicted unknown boundary conditions. This example is extended to consider spatial grid changed and temporal dependence on the numerical solution using moving finite element method [38].


*2.2. Concrete Composition and Properties' Test Methods*

Based on Portland multicomponent cements CEM II/C-M and multicomponent cements CEM VI, concrete mixes with the following composition, given in Table 4, were designed.

**Table 4.** Mix proportions of concrete mixtures.

Two types of concrete were prepared—type I containing 300 kg of cement in 1 m3 of concrete mix at a ratio w/c = 0.60 and type II, containing 340 kg of cement in 1 m3 of concrete mix at a ratio w/c = 0.35. Natural gravel aggregate with a fraction up to 16 mm and sand 0–2 mm as fine aggregate were used in the concrete mixture. A superplasticizer (PCE) based on polycarboxylate ether was used in the composition of concrete with reduced water–cement ratio (w/c = 0.35).

The properties of concrete mixtures and hardened concrete were tested according to the methodology included in the standards, which are presented in Table 5.

**Table 5.** Procedures used to determine the properties of the concrete mixture and hardened concrete.

#### **3. Results and Discussion**

#### *3.1. Properties of CEM II*/*C-M and CEM VI Cements*

The properties of the cements are presented in Table 6. The density of the cements was lowest for those containing siliceous fly ash (Table 6). The specific surface area of ternary cements ranged from 4350 to 4750 cm2/g. Cement slurries with ternary cements did not show volume changes due to swelling (Table 6). The setting time of cements and other properties are closely related to their composition and the amount of mineral additives introduced (Table 6).

**Table 6.** Physical and mechanical properties of cements.

In most cases, the highest increases in strength of standard cement mortars can be observed between 7 and 28 days of curing (Figure 4). During this period, the strength increases quite significantly in the case of cements containing blast furnace slag (the slag is hydraulically active and begins to react with water a long time before the ash pozzolanic reaction begins). The highest strength increase in this period is observed in comparative slag cement C(55S) on Figure 4. Partial replacement of blast furnace slag, both with limestone LL and fly ash V, slightly reduces the strength increase between the 7th and 28th days of hardening. Omitting the small influence of limestone on the increase in early strength, it is a rather chemically inert component in the cement system, and therefore its addition to slag causes a decrease in later strength. Replacement of slag with fly ash also slows down the dynamics of strength growth. This can be explained by the fact that the pozzolanic reaction of fly ash begins intensify only after 28 days of curing (when the amount of Ca(OH)2 from cement hydration increases). The final strength (after 360 days) of multicomponent cement C(30S-10LL) is similar to that of comparative cement C(55S), while in the case of cement C(35S-20V) there is a slight decrease in the final strength, compared to cement C(55S) (Figure 4). This decrease can be explained by the lower activity of fly ash in relation to ground granulated blast furnace slag, which is a component with latent hydraulic activity (with a CaO content of approximately 40–44% and after heat treatment in a blast furnace under conditions similar to those in a rotary kiln for Portland clinker production).

The partial replacement of fly ash by limestone C(30V-10LL) in cement composition, allows a cement to be made with higher early strength (after 2 days) and higher final strength than the reference cements C(40V) and C(40LL). The higher early strength in the presence of limestone may result from the caulking effect as well as the small amount of carboaluminates formed. On the basis

of the results obtained, it can also be observed that the addition of LL limestone decreases the strength of cement mortars to a greater extent in combination with siliceous fly ash (C(30V-10LL)), while the use of limestone (even up to 20%) in combination with ground granulated blast furnace slag (cements: C(30S-10LL), C(35S-20LL)) gives a much smaller decrease, slightly less than in the case of using the S slag composition with fly ash V-cement C(35S-20V).


**5.2 Large incisional hernia**

In our institution we prospectively evaluated 125 with a hernia diameter ≥5cm among 428 patients undergoing incisional hernia repair. We demonstrated that laparoscopic repair of large incisional hernias is technical feasible and associated with less SSI and shorter hospital stay but a comparable recurrence rate as open hernia repair (Table 2) [11].

Laparoscopic Incisional Hernia Repair 187

space SSIs are defined as infections in any organ or space. In laparoscopic incisional hernia repair the incidence of SSI is low. In a meta-analysis of 8 randomized controlled trials Forbes et al. showed a significant reduced risk of surgical site infections in laparoscopic incisional hernia repair compared to open surgery [18]. The extensive tissue dissection which is associated with the open approach explains the significant higher infection rate in open surgery. Mostly SSIs in laparoscopic surgery are superficial and can be treated

In general the mortality rate of laparoscopic incisional hernia repair is low with 0.05% [8]. The most serious complication during laparoscopic incisional hernia repair is enterotomy [8]. Enterotomy occurs during adhesiolysis or as a burning lesion with the electorcauter. Therefore we avoid electrocauterisation during adhesiolysis to prevent bowel lesions and perforation. The incidence of intraoperative bowel injuries has been reported to be 1.78% [20] A recognized enterotomy during the operation is associated with a mortality rate of 1.7% [20]. However, if the enterotomy is not recognized during the operation the mortality rate is increased up to 7.7% [20]. Enterotomy can be repaired by laparoscopic or open

Enterocutaneous fistula after intraperitoneal non-resorbable mesh implantation was first reported in by Kaufman et al. in 1981 [21]. An overview of the current literature shows that enterocutaneous fistula after incisional hernia repair is a rare complication and occurs in up to 1% [22]. There was no association of enterocutaneous fistula if the omentum was placed between the mesh and bowel or not. In cases of enterocutaneous fistula the mesh has to be resected partially around the fistula. Complete mesh removal is very rare and depends on

Lomanto et al. showed that there is no difference in the amount of pain comparing laparoscopic and open hernia repair at 24 and 48 hours postoperatively [24]. However, patients undergoing laparoscopic repair had significantly less pain at 72 hours compared to

The threshold for chronic pain is set at three months postoperatively according to the International Association for the Study of Pain [25]. There is no meta-analysis investigating chronic pain after laparoscopic incisional hernia repair. Postoperative pain after mesh fixation with transfascial sutures is likely due to nerve irritation or entrapmen [26]. There is a randomized controlled trial investigating pain comparing two different techniques of mesh fixation [26]. Postoperative pain following suture fixation was significantly higher at 6 weeks postoperatively and two patients suffered from nerve irritation at sites of sutures. However, after 6 months, no difference was seen between the two groups. Pain after mesh fixation with transfascial sutures is likely due to nerve irritation or entrapment and the relatively small distance between individual sutures used in this study. The significant reduction of pain between 6 weeks and 6 months post operation in these patients could be in response to desensitisation of entrapped nerve fibres or in response to resolution of local

open surgery allowing earlier discharge and return to work [24].

conservatively. Mesh removal due to an surgical site infection is very rare [19].

**6.4 Enterotomy**

approach with similar outcome result [20].

**6.5 Enterocutaneous fistula**

the surgeons experience [23]

**6.6 Pain**

Values in parentheses are percentages unless indicated otherwise. \* Values are median (range).

Table 2. Results of outcome parameters of large incisional hernia repair


**2. The healthy right and left ventricles**

Although many similarities exist between the ventricles, and they work in concerted effort to efficiently contract and relax for sufficient blood delivery, important embryological, physiological, and pathophysiological differences exist between the right and left ventricles [8]. We will briefly discuss a few of these differences, with a specific focus on mitochondria and metabolism.