Assessing the drinking water quality in the Inner Mongolia Autonomous Region from 2014 to 2018

Drinking water of a suitable quality is essential for public health and safety. According to the World Health Organization (WHO) surveys, water pollution is attributed to 4.6% (123 million) disability-adjusted life-years (DALYs) and 3.3% (1.9 million) of global deaths worldwide (see https://www.who.int/publications/i/it-em/9789240013391; WHO 2019). It is reported that over 140 million people in 50 countries are drinking water containing excessive levels of arsenic (Wu 2020). In China, it is reported that over 40% of its rivers are heavily polluted and the serious water pollution caused about 190 million people to fall ill and 60,000 people to die from diseases such as liver and gastric cancers (see https://www.who.int/news-room/fact sheets/detail/arsenic; Tao & Xin 2014; WHO 2018). Poor quality of drinking water might contribute to diarrhea, intestinal parasite infections and some endemic disease such as endemic fluorosis, arsenicosis (Farías et al. 2021; Hajare et al. 2021; Monteiro De Oliveira et al. 2021; Khan et al. 2022). Therefore, a safe drinking water supply is one of the most effective means of promoting health and reducing poverty.

Inner Mongolia Autonomous Region located in the northernmost part of China accounts for 12.3% of China's land area and is the third largest province in China. Inner Mongolia Autonomous Region basically belongs to a plateau type geomorphology area, covering plateau, mountains, hills, plains, deserts, rivers, lakes and other geomorphology, with temperate continental climate as the main climate. There are four water systems in Inner Mongolia, including the Yellow River, the Erguna River, the Nenjiang River and the Xiliao River (Wang et al. 2011). Inner Mongolia is arid and semi-arid and the precipitation in the whole region gradually decreases from east to west, so the water resources are rich but the distribution is quite uneven (Zhao et al. 2015). Additionally, the soil belt is arranged in the direction of northeast to southwest, the most east is black soil belt, and the west is dark brown soil belt, chernozem soil belt, chestnut soil belt, brown loam belt, dark brown soil belt, gray calcium land belt, sandstorm land belt and gray brown desert land belt, which affects the main way of production (Zhao et al. 2015). The differences in geology and climate among the cities of Inner Mongolia variety the main production and life styles, which impact on water resources.

With a comprehensive understanding of conditions about drinking water quality among different city of the Inner Mongolia Autonomous Region, it will be possible to solve issues related to, and efficiently and accurately improve, the drinking water in different cities and from different water sources in the region. In this study, monitoring data for drinking water from 12 cities in the Inner Mongolia Autonomous Region for 2014 to 2018 were analyzed. The results from this analysis will provide the scientific basis for improving the drinking water quality.

The monitoring data of drinking water in 12 cities in the Inner Mongolia Autonomous Region from 2014 to 2018 were analyzed. The water samples collected included samples of Ex-factory water, Secondary-water-supply and pipe water from municipal water supply plants, independent water treatment plants and some self-built water plants during the dry and peak seasons. Secondary-water-supply refers to the centralized water supply which is re-stored, pressurized and disinfected or further treated before being delivered to customers through pipes or containers. This study includes 1,591 sampling points from 12 league cities in the Inner Mongolia Autonomous Region, supplying about 21 million people (Supplementary Material, Figure S1). When sampling, first open the tap water for 3–5 min, and then sample after replacing the new water. When collecting water samples of several kinds of test indexes from the same water source at the same time, the water samples for microbial index detection should be collected first. During sampling, the sterilized sampling bottles should not be washed with water samples, and fingers and other articles should be avoided from staining the bottle mouth. For the water samples used for the detection of physical and chemical indicators, wash the container and plug with the water samples to be tested 2∼3 times before sampling, and collect the water samples to the bottle shoulder. Sampling volume and preservation method of drinking water monitoring index are shown in Supplementary Material, Table S1 (GB/T 5750.2-2006). The chroma, turbidity, conductivity, PH value and residual chlorine of the water samples were detected in the sampling site, and other monitoring indexes were monitored in the local laboratory. Water samples should be kept in accordance with the corresponding monitoring indicators preservation conditions, to ensure the stability of detection index.

The data were grouped and three different indexes were calculated, namely a microbiological index, a sensory trait and general chemical property index, and a toxicological index. The microbiological index comprised data for total coliforms, heat-resistant coliform bacteria, Escherichia coli, and the total number of bacteria. The sensory trait and general chemical index comprised color, turbidity, smell and taste, visible things, PH, aluminum, iron, manganese, copper, zinc, chloride, sulfate, soluble solids, total hardness and oxygen consumption. The toxicological index comprised arsenic, cadmium, chromium, lead, mercury, selenium, cyanide, fluoride and nitrate nitrogen.

During sample collection, physical parameters (PH), and total dissolved solids (TDS) were measured with an EC/PH meter. The samples were filtered through a 0.45 μm filter, collected in polyethylene terephthalate plastic bottles, acidified with concentrated HNO₃ to PH ≤ 2, and then stored at 4 °C until further analysis. The results were tested and evaluated in line with GB 5750.3-2006 (Supplementary Material, Table S2), the Standard Test Methods for Drinking Water, and GB 5749-2006 (Supplementary Material, Table S3), the Standards for Drinking Water Quality (Suvarna et al. 2020). When the data for all the variables were within the criteria of the standards, the sample was ‘qualified’. If the data for one of the variables of a water sample were unqualified, the water sample was evaluated as unqualified.

The overall WQI was the sum of these subindices for the variables. The values of the WQI were then classified into different categories (Kachroud et al. 2019), according to the WQI values water quality can be divided into five classifications. If WQI < 50, excellent; 50 ≤ WQI ≤ 100, good; 100 ≤ WQI ≤ 200, poor; 200 ≤ WQI ≤ 300, very poor; WQI ≥ 300, undrinkable.

The data were stored in an Excel 2010 spreadsheet and then were statistically analyzed using SPSS 25.0 (IBM). The percentage of qualified sample was compared using the chi-square test or Fisher's exact test in different years and regions. When P < 0.05, the results were considered statistically significant. ArcGIS was used to draw the distribution map of water sample collection points and the distribution map of sample detection results.

The values of the microbial, sensory trait and general chemical, and toxicological indexes for drinking water in the Inner Mongolia Autonomous Region have increased over the period from 2014 to 2018, and the differences between the three indexes for the different years were statistically significant (Figure 1) (all P-value < 0.0001). Of the three indexes, the percentage of qualified data was lowest for the toxicological index, and highest for the microbiological index.

The distribution of the qualified data for the three indexes in 12 of the league cities is shown in Figure 2. The microbiological index was highest in Alashan, the rates of qualified data for the sensory trait and general chemical index were higher in Xilingol League and Wuhai than in other areas. In Baotou and Xilingol, the percentages of qualified samples for the toxicological index were high. Drinking water in Chifeng was generally very suitable for drinking, and the three indicators were in the lowest range. As shown in Figure 3, the drinking water quality indexes for all the cities were in the excellent category (WQI ≤ 50). The WQI was further divided into four levels, according to the interquartile interval. The overall water quality was the best in Hinggan League and Chifeng, followed by Hulunbuir, Wulanchabu and Wuhai.

Table 1 shows the eligibility of various monitoring indicators of drinking water quality in the Inner Mongolia Autonomous Region from 2014 to 2018, including arsenic, cadmium, chromium, lead, mercury, selenium, cyanide, chroma, turbidity, smell and taste, visible objects, PH, aluminum, iron, copper, zinc and oxygen consumption, all of which reached the standard rate of no less than 95% during 2014 to 2018. Therefore, it is not listed in the figure. Sulfate, chloride, manganese, soluble total solids, total hardness of more than 90%, total coliform count and total bacterial count of less than 90% in 2014, since 2015, the rate of more than 90%. As can be seen from Figure 4, the compliance rates of fluoride and nitrate nitrogen were relatively low in 2014–2018.

As shown in Figure 5, the qualified rates for all three indexes were lower in rural areas than in urban areas, and the difference between them was statistically significant (all P-value < 0.0001).

The compliance of the three indexes for drinking water from different sources is shown in Table 1. The compliance of the microbial indexes of reservoir water and stream water was low, at only 47 and 62%, respectively. The compliance of the sensory trait and general chemical index for spring water, shallow well water, and stream water was low. The compliance of the toxicological index for shallow well and deep well water, and spring water was poor.

This analysis of the monitoring data for drinking water samples in the Inner Mongolia Autonomous Region from 2014 to 2018 shows that the compliance rate of the microbiology index was the highest of the three indexes. About 90% of the drinking water in Inner Mongolia may come from deep wells that are not susceptible to microbial contamination (Table 1). The compliance rate was lowest for the toxicological index, mainly because of the low compliance rate of fluoride and nitrate nitrogen (Figure 4). A comparison of the cities in Inner Mongolia shows that the number of fluoride and nitrate nitrogen index complied with the standard was low, reflecting the influence of geological factors and impact of human activities. High levels of fluoride in groundwater are found in many countries around the world, such as China, India, Pakistan and Tanzania (Cao et al. 2022; Khattak et al. 2022; Ijumulana et al. 2022). It is estimated that fluoride in drinking water affects numbers of people worldwide diagnosed with endemic fluorosis, which affects teeth and bones. The process of drinking water defluorination is very important to maintain population health. Nitrate in drinking water should be monitored closely, as it can cause cancer in humans when present at high concentrations (Han & Currell 2022). Nitrate nitrogen is introduced into groundwater from agricultural nitrogen fertilizer, human and animal manures, and soil humus (Han & Currell 2022). Denitrification technology, such as in situ biological denitrification and reactor biological denitrification, can be used to address the high concentrations of nitrate nitrogen in groundwater (Zhao et al. 2021). Furthermore, agricultural processes should be revised and nitrogen fertilizer inputs should be reduced, and human and animal manures should be stored and managed carefully to avoid polluting the water sources.

The values of the WQI, calculated from the data, indicate that the drinking water in the Inner Mongolia Autonomous Region is excellent. However, we found that more than 60% of the drinking water in Alashan has been conventionally treated (Supplementary Material, Figure S2), but the rate of microbial index exceeding the standard is still high. There was a significant difference in the qualified rate of biological indicators of water samples from the ex-factory water, the pipe water and the secondary-water-supply in Alashan (Supplementary Material, Table S4). This suggests that drinking water may have been contaminated by microorganisms during pipeline transportation or due to inadequate disinfection of the water in the water plant. The water plant should reform the drinking water transportation system, and at the same time, the water plant should appropriately increase the dose of ex-factory water disinfection or add secondary disinfection in the process of drinking water transportation. Firstly, water source protection facilities should be established to protect the water sources from pollution. Globally, at least 2 billion people use a drinking water source contaminated with feces (see https://www.who.int/publications/i/it-em/9789240013391), which poses a great threat to human health. Secondly, in view of the problem of high microbiological index of secondary-water-supply, the equipment of secondary-water-supply should be rectified, the dose of disinfectant should be appropriately increased, and the retention time of drinking water should not be too long to avoid secondary pollution (Ribas et al. 2000; Szczotko 2007). There were eight cities, including Hohhot, Baotou, Ordos, Bayinnaoer, Alashan, Xilingol, Chifeng, Wulanchabu, which failed to meet the standard for cyanide in drinking water by 85%. Studies have shown that cyanide exposure can affect thyroid function (Banerjee et al. 1997). The region should further investigate whether excessive levels of cyanide in drinking water could affect thyroid function. In addition, the local government should strengthen the investment in special treatment and advanced treatment of drinking water to improve drinking water quality and ensure the health of residents.

The quality of drinking water is lower in rural areas than in urban areas (Figure 5), perhaps because of less investment and funding for centralized rural water supplies, poor management of domestic waste, inadequate monitoring and supervision of regulations, and low awareness of the links between drinking water quality and public health. To address these issues, funds should be invested in projects to establish infrastructure for drinking water in rural areas, and government departments should proactively ensure that the regulations are met and should deliver public health education related to drinking water quality to the residents. Improved drinking water quality in rural areas will be beneficial for the health of farmers and rural dwellers.

The compliance with the standards of the drinking water quality indexes for water from different source types varied because of different pressures on the water sources. Surface water is very susceptible to changes in the environment and human activities (Yang et al. 2015). The quality of surface water and groundwater is easily affected by substances and transformations in chemicals, with effects on microbiological, toxicological, sensory and general chemical properties. The different water source types should be assessed and appropriate treatments should be adopted to treat the pollutants; for example, it may be necessary to apply a more intensive disinfection treatment to control the microbial pollution on surface water, so that the drinking water meets the standard. Similarly, groundwater should be treated with appropriate and advanced treatment methods to ensure that the drinking water is safe for residents (Nemcić-Jurec & Vadla 2010).

We thank Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac), for basic language editing of a draft of this manuscript.

N. Zhang and Y. Xia participated in study design. X. Wang and X. Q. Xu carried out data analysis and drafted the manuscript. X. Fang and X. G. Zhang assisted with data acquisition and interpretation, reviewed the manuscript and made revision of the manuscript. L. H. Li, Y. Liu and C. H. Gao collected and managed data. All authors read and approved the final manuscript.

The Inner Mongolia Autonomous Region Health and Family Planning Commission Research Project (grant number 201701041) and Million project of Inner Mongolia Medical University (grant number YKD2017KJBW010).

The authors declare that they have no competing interests.

All relevant data are included in the paper or its Supplementary Information.