Developing surface water quality standards in China

Su, Jing; Ji, Danfeng; Lin, Mao; Chen, Yanqing; Sun, Yuanyuan; Huo, Shouliang; Zhu, Jianchao; Xi, Beidou

doi:10.1016/j.resconrec.2016.08.003

Cited by 66 publications

(20 citation statements)

References 24 publications

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“…Eutrophication of aquatic systems is commonly caused by the unregulated discharge of agricultural irrigation water and domestic sewage that rich in nitrogen and phosphorus. Generally, their superfluous presence beyond threshold values in surface runoffs will mark stimulatory impacts on non-point eutrophication (above 2 mg L − 1 for ammonium (NH 4 -N) and 0.4 mg L − 1 for phosphorus (TP)) [1]. As a country dominated by the agricultural industry, China is in large uses of fertilizer containing nitrogen and phosphorus, posing a heavy burden in surface water regulation.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous adsorption study of ammonium and phosphate by ZnFe-layered double hydroxide (ZnFe-LDH)-modified adsorbents.

Liu¹,

Liang²,

Li³

et al. 2020

Preprint

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Background Trace amounts of nitrogen and phosphorus can easily trigger eutrophication damage in surface water, while cost-effective adsorption treatment is in prospect for clearing these pollutants simultaneously and efficiently. In this study, engineered adsorbents decorated with ZnFe-LDH by alkaline coprecipitation (3-6 mm, with modified ceramsite as CZF and modified volcanic rock as VZF) were prepared for NH 4 + and H 2 PO 4 - co-adsorption from aqueous solutions.Results Coexisting ions showed great effects on phosphate adsorption, especially Ca 2+ and CO 3 2- , and humic acid exhibited only a limited shielding impact on co-adsorption properties. Though comprehensive tests presented that the maximum captured amount of ammonium and phosphate occurred at pH 7, the isotherm and kinetic results suggest that two adsorbents preferentially adsorbed each pollutant. Specifically, the maximum uptake quantity of NH 4 + (15.55 mg-N g -1 ) and H 2 PO 4 - (11.21 mg-P g -1 ) were achieved by VZF and CZF, respectively, and controlled by physisorption and chemisorption distinctively, revealing that contaminants were cleared in disparate ways. Performances of seven consecutive adsorption/desorption cycles using 5% NaOH regenerant suggested that CZF retained 71.9% of PO 4 - removal efficiency, and VZF retained 47.9% of the NH 4 + adsorption rate, implying the strong reusability of ZnFe-LDH-modified adsorbents. A dynamic study has assessed that with 1 kg of combined modified adsorbents, approximately 527 L of polluted runoff flow could be continuously treated to below the National limits within one adsorption cycle.Conclusion Comparing with other parallel adsorbents, ZnFe-LDH-modified adsorbent is promising in eliminating eutrophication due to their superior capacity, stability, renewability, and non-toxicity.

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Section: Introductionmentioning

confidence: 99%

Simultaneous adsorption study of ammonium and phosphate by ZnFe-layered double hydroxide (ZnFe-LDH)-modified adsorbents.

Liu¹,

Liang²,

Li³

et al. 2020

Preprint

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“…Water-quality levels [1] are a systematic index for water-quality classification and assessment. The collected water-quality levels in the paper follow Chinese standard GB3838-2002 (Appendix A).…”

Section: Introductionmentioning

confidence: 99%

“…The collected water-quality levels in the paper follow Chinese standard GB3838-2002 (Appendix A). GB3838-2002 was promulgated by the Ministry of Urban and Rural Construction and Environmental Protection in light of environmental protection laws of the People's Republic of China [1]. The classification standards of water-quality levels in GB3838-2002 are different from standards of the United States, Japan, and Europe [1].…”

Section: Introductionmentioning

confidence: 99%

“…GB3838-2002 was promulgated by the Ministry of Urban and Rural Construction and Environmental Protection in light of environmental protection laws of the People's Republic of China [1]. The classification standards of water-quality levels in GB3838-2002 are different from standards of the United States, Japan, and Europe [1]. Water quality is classified using a single-factor method, which means a parameter that exceeds its corresponding criterion with the highest proportion is selected for water-quality-level classification.…”

Section: Introductionmentioning

confidence: 99%

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Water-Quality Classification of Inland Lakes Using Landsat8 Images by Convolutional Neural Networks

Ding

Chao

et al. 2019

Remote Sensing

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Water-quality monitoring of inland lakes is essential for freshwater-resource protection. In situ water-quality measurements and ratings are accurate but high costs limit their usage. Water-quality monitoring using remote sensing has shown to be cost-effective. However, the nonoptically active parameters that mainly determine water-quality levels in China are difficult to estimate because of their weak optical characteristics and lack of explicit correlation between remote-sensing images and parameters. To address the problems, a convolutional neural network (CNN) with hierarchical structure was designed to represent the relationship between Landsat8 images and in situ water-quality levels. A transfer-learning strategy in the CNN model was introduced to deal with the lack of in situ measurement data. After the CNN model was trained by spatially and temporally matched Landsat8 images and in situ water-quality data that were collected from official websites, the surface quality of the whole water body could be classified. We tested the CNN model at the Erhai and Chaohu lakes in China, respectively. The experiment results demonstrate that the CNN model outperformed widely used machine-learning methods. The trained model at Erhai Lake can be used for the water-quality classification of Chaohu Lake. The introduced CNN model and the water-quality classification method could cover the whole lake with low costs. The proposed method has potential in inland-lake monitoring.water-quality measurement, the cost is high, limiting the usage of in situ sampling and measurement. Optimization of a monitoring network is considered a trade-off between water-monitoring precision and cost [2]. A comprehensive and low-cost water-quality monitoring method was our goal.Remote-sensing monitoring of water quality and its parameters is considered as a promising and cost-effective monitoring method. There are many free-of-charge remote-sensing data, such as Landsat and Sentinel open-access data. Remote sensing provides a synoptic, repetitive, and consistent view of a water body. Water-quality-related variables, such as surface temperature, chlorophyll-a (Chl-a), turbidity and suspended solids (TSS) can be estimated from remote-sensing images according to their reflectance from the water surface [3]. The accuracy and stability of the remote-sensing inversion of surface-reflectance variables (Chl-a and SS) have improved after several years [4].Nonoptically active variables related to water pollution, such as total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), and dissolved oxygen (DO), cannot be directly sensed from water-surface reflectance because of their weak optical characteristics and low signal-to-noise ratio [3]. These nonoptically active variables are closely related to optically active parameters such as Chl-a, TSS, and colored dissolved organic matter (CDOM) [3,5]. Different kinds of regression models have been introduced to establish the relation between nonoptically active variables and optical active variabl...

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“…Assessment of ambient water quality determines its use for humans and ecological purposes. 1,2 Anthropogenic activities make the surface and ground water highly polluted 3 owing to the fact that surface water is extensively being used in industrial activities, agriculture sector, domestic and municipal facilities. As clean water is highly demanded, it can be derived from various sources but unfortunately, surface waters most often have threat of begin polluted and their low quality status leads to public health issues.…”

Section: Introductionmentioning

confidence: 99%

Spring Water Quality and Human Health: An Assessment of Natural Springs of Margalla Hills Islamabad Zone-III

Batool¹,

Samad²,

Kazmi³

et al. 2018

IJH

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Water is the earth's most valuable compound that is fundamental for humans as well as all other living forms and seems to be inexhaustible. Unfortunately the outlook for the world's fresh water supply is not very hopeful. Moreover shortage of fresh water throughout the world can be directly attributed to human misuse in the form of pollution. Water is used for number of purposes like drinking, bathing and washing etc. so it must be free from toxic materials for healthy human and aquatic life. Among surface waters, springs' water is usually considered as safe for drinking. In the present study, springs' water of Margalla Hill Zone III Islamabad was assessed to clarify the concern about the quality and safety of this water used for drinking purposes in terms of physico-chemical (color, temperature, pH, odor, turbidity, hardness, TDS, EC, alkalinity, DO, Cl -, NO 2 -, NO 3 2-, SO 4 2-, heavy metals) and microbiological parameters (total Coliform, Pseudomonas aeruginosa, Enterococcus and Staphylococcus auerus). For this purpose, 15 water samples were collected from five different sites of Margalla Hills. Results showed that WHO drinking water standards were exceeded for EC, DO, cadmium, lead and microbiological parameters which may be detrimental for human health if water is consumed on daily basis. All other selected parameters did not exceed WHO drinking water standards and therefore, water from the sampling area does not pose any significant threat to consumer's health.

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Developing surface water quality standards in China

Cited by 66 publications

References 24 publications

Simultaneous adsorption study of ammonium and phosphate by ZnFe-layered double hydroxide (ZnFe-LDH)-modified adsorbents.

Simultaneous adsorption study of ammonium and phosphate by ZnFe-layered double hydroxide (ZnFe-LDH)-modified adsorbents.

Water-Quality Classification of Inland Lakes Using Landsat8 Images by Convolutional Neural Networks

Spring Water Quality and Human Health: An Assessment of Natural Springs of Margalla Hills Islamabad Zone-III

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