INTRODUCTION

Environmental pollution is often linked to the growth of economic activities and industrialization (Carvalhoet al., 2018; Tranet al., 2019; Nasrollahiet al., 2020). Manufacturing and mining industries are the primary economic sectors in the Asian region that generate different types of pollutants. Industrial activities have been known to contaminate rivers around the business district (Vuet al., 2017; Liet al., 2019; Hoanget al., 2020), including those of the oil and gas sector that potentially diminish the water quality near and downstream of its operational areas. For instance, crude oil extraction brings water to the surface, termed produced water (PW), which constitutes more than 80% of the total wastewater (Bagheriet al., 2018) and contains hydrocarbons and their derivatives. PW is often discharged into the ocean from offshore operations (Jepsenet al., 2018), which can pollute the marine environment, a problem frequently caused by the oil and gas industry that should be handled seriously (Carpenter, 2019). Similarly, on-shore operations often release PW into rivers (McLaughlinet al., 2020). Introducing pollutants into a river can have vast adverse impacts on the ecology and the surrounding communities that depend on its water and many other benefits (Khan and Zhao, 2019). Therefore, PW and other domestic wastes generated by the oil and gas industry should meet a certain standard of quality prior to disposal or reuse (Patimahet al., 2022). According to many previous studies, PW can be utilized to irrigate food crops and other agricultural plants on dry terrains (Echchelhet al., 2018; Sedlackoet al., 2019; McLaughlinet al., 2020). For this purpose, PW is commonly treated using produced water reinjection (PWRI) by adsorption (Costaet al., 2022). However, this method can damage the reservoir formations if it is not conducted carefully and in compliance with the procedures (Lianget al., 2018). It is necessary to be vigilant even when existing processing technologies and processes have been shown to meet the quality criteria, mainly because PW is generated daily in a large volume and can thus endanger the ecosystem around the production area (Ganiyuet al., 2022). PW management requires a structured framework and a risk-based strategy and incorporates various issues, including environmental, technical, and financial (Ghafooriet al., 2022). In some cases, it solely relies on the most cost-efficient alternative (Sabieet al., 2022). Subpar management practices can reduce soil fertility, microbial diversity, agricultural yields (Milleret al., 2020), and lead to river pollution. Therefore, river segments near and downstream of oil and gas fields should be regularly inspected to ensure the water quality standard is met. The water quality index (WQI) is often proposed to estimate and monitor water quality (Aliyuet al., 2019; Lkret al., 2020). However, because the quality standards vary across countries and purposes, the estimation method should refer to or be adjusted to local government regulations (Costaet al., 2022). For instance, in Indonesia, one of the techniques used to assess river water quality is the pollution index (PI), as outlined in the Decree of the Minister of the Environment No. 115 of 2003 (Hamuna and Tanjung, 2021; Wikurendraet al., 2022). This study primarily aimed to evaluate the river water quality using PI. Samples were collected along the Cangkring River segment near the Mudi Field in 2021. It is one of the locations in Tuban, East Java, Indonesia, where the oil and gas industry operates.

MATERIALS AND METHODS

Bengawan Solo River and one of its tributaries, Cangkring River, run close to the Mudi Field, an oil and gas exploration site in Tuban Regency, East Java Province, Indonesia. The field lies between 7^o 04’41” and 7^o 08’45”S and between 111^o 57’02” and 111^o 59’46”E (Fig. 1). It is about 32 km from Tuban Regency and 101 km from Surabaya City, the capital of East Java Province. Tuban has two seasons during which various disasters have been reported: drought and forest fires in dry seasons and floods and landslides in multiple places in rainy seasons (Rustinsyahet al., 2021). It is one of the regencies in the province that relies on agricultural commodities, and the livelihood of its people is mostly in the farming sector (Widiatmakaet al., 2016).

Fig. 1. Geographical location of the Cangkring River, Indonesia, along with the seven sampling points

Water sampling

Samples were collected from January to September 2021 at several points along the Cangkring River segment near the oil and gas production site (Mudi Pad B) and the office areas (Mudi Pad A and Mudi Pad C) (Fig.1). The sampling points were selected based on their turbidity level and their position relative to potential sources of pollutants. Different hypotheses were formulated for each point so that the data obtained could describe the entire study area. Table 1 describes the condition and the hypothesis of each sampling location.

Test parameters and quality standards

The water samples collected at seven points were tested ex-situ at the Hydrology Laboratory, Gadjah Mada University, Yogyakarta, Indonesia. The primary characteristics used to gauge the water pollution level were total dissolved solids (TDS), total suspended solids (TSS), biological oxygen demand (BOD₅), chemical oxygen demand (COD), oil and grease, and total coliform, on which the test parameters were based. Three of the seven sampling points, namely SW1, SW2, and SW7, were in direct contact with Mudi Pad B (oil and gas production site) and were assumed to have a higher pollution potential than other points. Thirteen additional organic chemical parameters, including pH, nitrate, nitrite, chloride, sulfate, ammonia, phosphate, detergent, hexavalent chrome, cadmium (Cd), lead (Pb), zinc (Zn), and copper (Cu), were tested at these points. Table 2 summarizes the test parameters, units of measurement, and standards or requirements for the river water quality. These parameters were assessed using specific methods according to applicable laws and regulations (MLHK, 2016). All parameter values were compared against their respective quality standards for class III purposes according to Government Regulation Number 82 of 2001 because the Cangkring River was designated for agricultural activities. Water quality standards measure the highest amount or level of substances, energy, living organisms, or other components a body of water can tolerate without changing its desired condition for specific utilization.

Calculation of the pollution index value

According to the ministerial decree, PI is a method used to assess the river water quality in Indonesia (Hamuna and Tanjung, 2021; Wikurendraet al., 2022). It calculates the pollution level of a water body in relation to water quality parameters measured directly in the field or assessed in the laboratory using collected water samples (Martinuset al., 2018; 3Suriadikusumahet al., 2021). However, unlike the water quality index, PI is produced to inform about the designated uses of one segment or the entire body of water (Effendiet al., 2015). In other words, it decides the water quality status for a specific purpose (Ikhsanet al., 2021) and lays the groundwork for improving water quality due to high pollutant content (Rahmatillahet al., 2021).

Following the ministerial decree, the pollution index (PI) was used to generate and analyze the water quality parameter values at each sampling point in the Microsoft Excel program. In this study, the PI value was calculated using Eq. 1 (MNLH, 2003).

Where, L_ij is the maximum allowable concentration of water parameter (i) for designated use (j), C_i is the value of the water parameter (i) based on the test results, PI_j is the pollution index for designated use (j), M on C_i/L_ij is the highest value, and R on C_i/L_ij is the average value.

The level of damage or water pollution is difficult to determine if two C_i/L_ij values are close to the reference value (1.0), e.g.,C₁/L_1j = 0.9 and C₂/L_2j= 1.1, or if they are substantially different, e.g., C₃/L_3j = 5.0 and C₄/L_4j= 10.0. The points below should be considered in solving these problems:

1) If C_i/L_ij < 1.0, then the PI is the same as the measurement result

2) Suppose C_i/L_ij > 1.0. In that case, (C_i/L_ij)_New is calculated using Eq. 2 (MNLH, 2003). P is a constant, and its value can be flexibly chosen depending on the results of environmental observations and the intended criteria for a designated use. The commonly used P value is 5.

The derived PI values were then converted into water quality status, which indicates if a body of water is suitable for a particular purpose or polluted at a predefined time (MNLH, 2003). Table 3 classifies the status into four: good condition for PI smaller than 1, slight, moderate, and heavy pollution for PI larger than 1. Each water quality parameter directly correlates to and strongly influences the PI value.

RESULTS AND DISCUSSION

River water quality

Table 4 shows the water quality test results of the Cangkring River between January and September 2021. Seven water samples were collected from different sites along the river segment near the oil and gas production site and office areas and analyzed using six physical, chemical, and microbiological parameters (see Table 2). The two physical parameters, TDS and TSS, were 146–682 mg/L and 12–36 mg/L, or below the upper threshold of 1,000 and 400 mg/L for class III purposes. TDS is influenced by several anthropogenic and natural activities on the surface, while TSS is determined by plant roots and their role in nutrient adsorption, dust distribution from the air, and root decomposition (Suriadikusumahet al., 2021). The chemical parameters tested were BOD₅, COD, and oil and grease contents. BOD₅ values varied widely from 1.70 to 20.60 mg/L. SW1, SW4, SW5, and SW7 had BOD₅ above its maximum allowable presence for class III purposes. Moreover, SW7 had the highest BOD₅ of 20.6 mg/L or three times greater than the upper limit. The cause is impurities from agricultural and domestic waste disposed of into the river. On the contrary, the COD values of all the points were below the upper limit. Nevertheless, there is a linear relationship between COD and BOD₅ (Qiet al., 2021). The next chemical parameter was oil and grease content, which exceeded its maximum allowable presence at SW1, SW2, and SW3. The only microbiological parameter tested in this study was total coliform, and the results showed that it was below the upper threshold of 10,000 per 100 mL at all the sampling points. Based on the physical and microbiological parameter values, the Cangkring River segment near the oil and gas production site and office areas still meets the water quality standards and is thus suitable for supplying agricultural irrigation water. However, the chemical conditions put a limit to this purpose because the upper thresholds were exceeded at SW1, SW2, and SW7, which were close to Mudi Pad B (production site). Of the seven points, SW6 is the only location whose parameter values were below their respective maximum allowable presence. It is located between Mudi Pad B (production site) and Mudi Pad C (office area) and receives water from other sources.

Additional testing of chemical parameters

Because the BOD₅ and oil and grease content at SW1, SW2, and SW7 exceeded their maximum allowable presence for class III purposes, the three points were further tested using 13 additional organic chemical parameters. Their selection for the additional test was also based on their proximity to the potential sources of pollutants. SW1 and SW2 were in direct contact with the oil and gas production site Mudi Pad B, while SW7 was located between Mudi Pad B and the office area Mudi Pad A. In addition, they had a higher pollution potential than the other four sampling points, and SW7 had a slightly higher value than the rest for some parameters. Of the 13 additional parameters, the nitrite, ammonia, and phosphate concentrations exceeded their respective upper limits for class III purposes, as shown in Table 5.

Pollution index and water quality status

PI values determine the river’s water quality at each sampling location based on their physical, chemical, and microbiological parameter values (see Table 4). The PI of each parameter was calculated using Eqs. 1 and 2 to obtain the value of C_i/L_ij and (C_i/L_ij)_New for class III purposes, i.e., agricultural irrigation, before being classified into one of the four water quality statuses (see Table 3). Table 6 shows the entire calculation results for the six parameters and the water quality status of each point. Tables 4 and 6 also indicate a linear relationship between the parameter values, PI values, and water quality status. The water quality test results showed that SW6 was the only point that met all the criteria for class III water. Similarly, its PI value, 0.558, categorized the water quality as good condition. On the contrary, the PI values of other points ranged from 1.080 to 1.522, indicating slight pollution. This pollution level is also characterized by the PI value of each tested parameter. For instance, BOD₅ and oil and grease content at other locations had a PI value of between 1 to 5, contributing to slight pollution. The sampling points other than SW6 were classified as slightly polluted, with the primary contributing factors being BOD₅ and oil and grease content because only both parameters had the C_i/L_ij and (C_i/L_ij)_New of higher than 1.

Table 7 shows the PI calculation for the six parameters measured at the initial stage and the additional 13 chemical parameters at SW1, SW2, and SW7. Compared with the PI values of the six parameters (Table 6), there was a considerable increase in value and water quality status from slight to moderate pollution. The three selected points were previously identified as potentially polluted by the production activities of the oil and gas sector because BOD₅ and oil and grease content had the C_i/L_ij and (C_i/L_ij)_New of higher than 1 (see Table 6). Aside from these two chemical parameters, the additional test also revealed that nitrite, ammonia, and phosphate contributed to the high PI values. However, nitrite and ammonia contents (dissolved nitrogen) were found to be substantially above their upper limits for class III water. The total nitrogen calculated using Total Kjeldahl Nitrogen (TKN) includes ammonia and all organic nitrogen molecules that can cause the formation of a hypoxic zone, resulting in oxygen deprivation (Al-Ghoutiet al., 2019). The high nitrite contents indicated that the organic matter breakdown along the Cangkring River segment consumed oxygen, thereby decreasing the oxygen content in the water. Meanwhile, an increase in nitrogen levels, specifically nitrite, is caused by the influx of waste from agricultural activities (Johnet al., 2020).

The average and maximum C_i/L_ij and/or (C_i/L_ij)_New values of all the parameters are components of PI calculation formula. PI values determine the water quality status; thus, if one parameter value increases to very high, it will also increase the PI value and worsens the status. The maximum C_i/L_ij and/or (C_i/L_ij)_New and/orvalues of nitrite and ammonia were higher than 5, indicating moderate pollution. Both parameters caused the water quality status at SW1, SW2, and SW7 to change from slightly to moderately polluted. Nitrite and ammonia, which include nitrogen, are not always produced by the oil and gas industry but can also result from agricultural practices that apply nitrogen-based fertilizers. Even though nitrite and ammonia are non-carcinogenic, their high presence in moderately contaminated water is still harmful to human health (Adimalla and Qian, 2019). Nevertheless, Cangkring River water can still be used for agricultural irrigation, provided that a further investigation into the effect of high nitrate and ammonia content on plant growth be conducted.

CONCLUSION

The water quality of the Cangkring River segment near the oil and gas fields has been determined at seven sampling points using six main physical, chemical, and microbiological parameters, i.e., TDS, TSS, BOD₅, COD, oil and grease, and total coliform. Furthermore, points SW1, SW2, and SW7 have been selected for further analysis using 13 more chemical parameters because of their high BOD₅ and oil and grease levels and proximity to the production site and office areas. Based on the additional analysis, the river’s nitrite, ammonia, and phosphate concentrations are above their maximum allowable presence in water for class III purposes. For these reasons, their water quality status is moderately polluted. The nitrite and ammonia contents are substantially above their upper limits, presumably caused by an increase in nitrogen. Nitrite and ammonia are not always associated with the oil and gas industry but also agricultural activities. Nevertheless, the Cangkring River water can still be used to irrigate farmlands despite its low to moderate contamination levels. The research has found that even with the strict regulations currently enforced in treating the produced water (PW) from the oil and gas fields, the discharged PW still contains a significant amount of nitrite and ammonia, resulting in moderately polluted river water. Also, conducting an additional test with 13 chemical parameters at three locations closest to the fields has provided a good comparison for the six-parameter water quality test results and confirmed this finding. Therefore, to address the high nitrite and ammonia contents, it is also necessary to regularly assess the river water quality near the fields to ensure that it is safe for the agricultural sector and the environment and to investigate the effect of moderately contaminated water on crop health.

AUTHOR CONTRIBUTIONS

A.S. Patimah conducted the literature review, designed the research, performed data collection, data analysis and interpretation, and prepared the article. A. Prasetya performed the literature review for chemical parameters and analyzed and interpreted the data, especially on the water test results. S.H.M.B. Santosa conducted the literature review for site selection for the research, sampling, and data collection and analyzed and interpreted the data, especially those related to location and mapping.

ACKNOWLEDGMENT

The authors would like to express their gratitude to the Doctoral Program in Environmental Sciences at Gadjah Mada University in Yogyakarta, Indonesia, for funding this research through the dissertation research grant program (PDD) in 2022 [Grant Number 1873/UN1/DITLIT/Dit-Lit/PT.01.03/2022]. Gratitude is also extended to the Hydrology Laboratory of Gadjah Mada University and Pertamina LLC in Tuban for their support in acquiring field data and test results.

CONFLICT OF INTEREST

The authors declare no potential conflict of interest regarding the publication of this work. In addition, the ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, and redundancy, have been completely witnessed by the authors.

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ABBREVIATIONS

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