Environmental prioritization of pesticide in the Upper Citarum River Basin, Indonesia, using predicted and measured concentrations

Removal of multiple pesticides from water by different types of membranes

Pesticides are used in agriculture to protect crops from pathogens, insects, fungi and weeds, but the release of pesticides into surface/groundwater by agriculture runoff and rain has raised serious concerns not only for the environment but also for human health. This study aimed to investigate the impact of surface properties on the performance of seven distinct membrane types utilized in nanofiltration (NF), reverse osmosis (RO) and forward osmosis (FO) processes in eliminating multiple pesticides from spiked water. Out of the membranes tested, two are self-fabricated RO membranes while the rest are commercially available membranes. Our results revealed that the self-fabricated RO membranes performed better than other commercial membranes (e.g., SW30XLE, NF270, Duracid and FO) in rejecting the targeted pesticides by achieving at least 99% rejections regardless of the size of pesticides and their log Kow value. Despite the marginally lower water flux exhibited by the self-fabricated membrane compared to the commercial BW30 membrane, its exceptional ability to reject both mono- and divalent salts renders it more apt for treating water sources containing not only pesticides but also various dissolved ions. The enhanced performance of the self-fabricated RO membrane is mainly attributed to the presence of a hydrophilic interlayer (between the polyamide layer and substrate) and the incorporation of hydrophilic nanosheets in tuning its surface characteristics. The findings of the work provide insight into the importance of membrane surface modification for the application of not only the desalination process but also for the removal of contaminants of emerging concern.

Assessing city-wide pharmaceutical emissions to wastewater via modelling and passive sampling

With increasing numbers of chemicals used in modern society, assessing human and environmental exposure to them is becoming increasingly difficult. Recent advances in wastewater-based epidemiology enable valuable insights into public exposure to data-poor compounds. However, measuring all >26,000 chemicals registered under REACH is not just technically unfeasible but would also be incredibly expensive. In this paper, we argue that estimating emissions of chemicals based on usage data could offer a more comprehensive, systematic and efficient approach than repeated monitoring. Emissions of 29 active pharmaceutical ingredients (APIs) to wastewater were estimated for a medium-sized city in the Netherlands. Usage data was collected both on national and local scale and included prescription data, usage in health-care institutions and over-the-counter sales. Different routes of administration were considered as well as the excretion and subsequent in-sewer back-transformation of conjugates into respective parent compounds. Results suggest model-based emission estimation on a city-level is feasible and in good agreement with wastewater measurements obtained via passive sampling. Results highlight the need to include excretion fractions in the conceptual framework of emission estimation but suggest that the choice of an appropriate excretion fraction has a substantial impact on the resulting model performance.

Proposal for priority emerging pollutants in the Nakdong river, Korea: Application of EU watch list mechanisms

The Nakdong River, the longest in Korea, has received numerous pollutants from heavily industrialized and densely populated areas while being used as a drinking water source. A number of research have reported occurrences of emerging pollutants (EPs) in the river. The results requested efficient monitoring and systematic management strategies such as EU watch list under Water Framework Directive. The aim of this study is to propose a watch list through preliminary monitoring of the river and risk-based prioritization approach. As candidates for monitoring target, 632 substances were selected based on literature and database searches. Among them, 175 substances were subjected to target screening method whereas 457 were evaluated via suspect screening. A risk-based prioritization was applied to substances quantified through target screening based on concentrations, and a scoring-based prioritization was applied to substances tentatively identified through suspect screening. Sampling campaigns (n = 12) were conducted from October 2020 to September 2021, at 8 sampling sites along the river. As a result, 130 target substances were quantified above the LOQ. Among the 21 substances whose priority score was assigned through risk-based prioritization, telmisartan and iprobenfos were identified with very high environmental risk while candesartan, TBEP, imidacloprid, azithromycin and clotrimazole were classified with high or intermediate risk. As result of the scoring system for 39 tentatively identified substances, 6 substances (benzophenone, caprolactam, metolachlor oxanilic acid, heptaethylene glycol, octaethylene glycol and pentaethylene glycol), which were then confirmed with reference standards, showed a potential environmental risk. Those substances prioritized through target and suspect screening followed by scoring systems can be a subset for the watch list and potential targets for nationwide water quality monitoring program in the future.

Mapping domestic water use to quantify water-demand and water-related contaminant exposure in a peri-urban community, Indonesia

Water use of domestic activities was quantified by interviewing 217 people in a peri-urban community near Bandung, Indonesia. Resulting in data on domestic water demand and data needed for exposure modelling of domestic activities: drinking, cooking, brushing teeth, swimming, bathing, laundry, dishwashing, religious cleansing, washing hands and cleaning food. Average total domestic water usage was 117 l/person/day, topping the WHO guidelines for basic needs (50-100 l/person/day). This water use level is comparable with higher income countries for the same set of activities but 100% higher than water use in an Indonesian traditional rural community. The final dataset provides insight in quantity of water used for domestic activities, as well as the use-frequency, duration and water sources used. These data are scarce for Indonesia and other low-middle income countries but necessary for water demand studies and estimating risks through exposure to pathogens and emerging contaminants in human exposure modelling.

Estimating the temporal and spatial distribution and threats of bisphenol A in temperate lakes using machine learning models

Bisphenol A (BPA) is easily enriched in many human-disturbed watersheds, particularly lakes with poor water mobility, which is posing a threat to aquatic biota. While previous studies have focused on the concentration of BPA in water and its toxicity to aquatic organisms, a small amount of measured data is not enough to reveal the temporal and spatial distribution and threats of BPA, and estimate the ecological risk in watersheds. Therefore, we collected 164 measured BPA data points from Taihu Lake to develop machine learning models using random forest (RF), support vector machine (SVM) and least square regression (LSR) and created month-by-month watershed prediction maps in temperate lakes to estimate the spatiotemporal distribution and threats of BPA. Due to RF's superior robustness to noisy data, the RF model exhibits the best performance among the three algorithms. The RF model showed acceptable predictive performance on the modeling dataset (coefficients of determination and root-mean-square error for the training set were 0.927 and 17.499, respectively, and 0.607, 39.645 for the validation set, respectively). The maps indicated that areas susceptible to anthropogenic activities were more severely polluted by BPA, and rainy climate may favor the migration of BPA to aquatic ecosystems. The model was also applied to predict 42 data points of BPA collected from Dianchi Lake, and the results showed that most predicted data were within a factor of 10 of the measured data, but the prediction accuracy of the model has declined. The ecological risks in the two lakes were evaluated and attention should be paid to the regions with higher risks. Our study provided a novel idea for comprehensive monitoring of an unconventional trace pollutant with endocrine disrupting effects in aquatic ecosystems and analyzing their spatiotemporal distribution, which will contribute to the scientific assessment of the ecological risk of BPA.

Emissions of pharmaceuticals and plant protection products to the lagoon of Venice: development of a new emission inventory

Estimating the emissions of chemical pollutants to water is a fundamental step for the development and application of effective and sustainable management strategies of water resources, but methods applied so far to build chemicals inventories at the European or national scale show several limitations when applied at the local scale. The issue is particularly relevant when considering contaminants of emerging concern (CECs), whose environmental releases and occurrence are still poorly studied and understood. In this work, an approach to estimate water emissions of nine active pharmaceutical ingredients (APIs) and ten most applied plant protection products (PPPs) is presented, considering proxy indicators (e.g., sales data and census information). The application area is the lagoon of Venice (Italy), a complex transitional environment highly influenced by anthropic pressures (e.g., agricultural and industrial activities, animal breeding, and wastewater discharge). The presented approach can be tailored to the information available for any local scale case study. Data on annual regional sales of PPPs and APIs were integrated with georeferenced demographic and economic statistics (such as census and land-use information) to estimate chemicals emissions to surface water and groundwater. A sensitivity and uncertainty analysis identified the main factors affecting emissions estimates, and those contributing more significantly to results uncertainty. Results showed the highest estimated emissions of APIs for antibiotics (i.e., amoxicillin, clarithromycin, azithromycin, and ciprofloxacin) used for humans and animals, while most of hormones' emission (i.e., 17- α-ethinylestradiol and 17-β-estradiol) derived from animal breeding. Regarding PPPs, glyphosate and imidacloprid emissions were one to two orders of magnitude higher compared to the other chemicals. Uncertainty and sensitivity analysis showed that the variability of each parameter used to estimate emissions depends greatly both on the target chemical and the specific emission source considered. Excretion rates and removal during wastewater treatment were major key parameters for all the target pharmaceutical compounds, while for PPPs the key parameter was their loss into the natural waters after application.

Chlorination disinfection by-products in Southeast Asia: A review on potential precursor, formation, toxicity assessment, and removal technologies

This review discusses disinfection by-products' (DBPs) potential precursors, formation, and toxicity, alongside available research on the treatment of DBPs in Southeast Asian countries' water sources. Although natural organic matter (NOM) in the form of humic and fulvic acids is the major precursor of DBPs formation, the presence of anthropogenic organic matter (AOM) also plays essential roles during disinfection using chlorine. NOM has been observed in water sources in Southeast Asian countries, with a relatively high concentration in peat-influenced water sources and a relatively low concentration in non-peat-influenced water sources. Similarly, AOMs, such as microplastics, pharmaceuticals, pesticides, and endocrine-disrupting chemicals (EDCs), have also been detected in water sources in Southeast Asian countries. Although studies regarding DBPs in Southeast Asian countries are available, they focus on regulated DBPs. Here, the formation potential of unregulated DBPs is also discussed. In addition, the toxicity associated with extreme DBPs' formation potential, as well as the effectiveness of treatments such as conventional coagulation, filtration, adsorption, and ozonation in reducing DBPs' formation potential in Southeast Asian sources of water, is also analyzed.

Contaminants of emerging concerns (CECs) in a municipal wastewater treatment plant in Indonesia

This study provides the first set of quantitative data on the occurrence and fate of a wide range of contaminants of emerging concerns (CECs) in Indonesia's largest wastewater treatment plant (WWTP). The WWTP employs waste stabilization ponds (WSPs) as the secondary treatment before discharging the effluent to the Citarum River. Fourteen out of twenty-two monitored CECs were detected in the wastewater influent, and seven were present in the effluent, with a total concentration of 29.8 ± 0.4 µg/L and 0.5 ± 0.0 µg/L, respectively. The occurrence of the CECs in this study was found to be well correlated with their possible use and known detection in surface waters in Indonesia. Caffeine (CAF) at 12.2 ± 0.1 µg/L, acetaminophen (ACT) at 9.1 ± 0.1 µg/L, N,N-diethyl-m-toluamide (DEET) at 5.0 ± 0.1 µg/L, ibuprofen (IBU) at 2.3 ± 0.0 µg/L, and triclosan (TCS) at 470 ± 64 ng/L were discovered as the five most prevalent CECs, followed by bisphenol A (BPA), trimethoprim (TMP), Tris(2-chloroethyl) phosphate (TCEP), sulfamethazine (SMZ), carbamazepine (CBZ), fluoxetine (FLX), benzotriazole (BTA), sulfamethoxazole (SMX), and metformin (METF). Biodegradable CECs (SMX, SMZ, ACT, IBU, TCS, BPA, CAF, DEET, and TMP) were efficiently removed (83-100%) by the WSP. In contrast, recalcitrant CECs achieved poor removal efficiencies (e.g., FLX at 24%), and for others, treatment processes even resulted in elevated concentrations in the effluent (CBZ by 85%, TCEP by 149%, and BTA by 92%). The CECs' influent concentrations were determined to pose a moderate aquatic cumulative risk, while no such risk was associated with their effluent concentrations. The study demonstrates the importance of conventional WWTPs in reducing the concentrations of CECs to minimize their aquatic contamination risk. The findings are relevant for countries, such as Indonesia, with limited resources for advanced centralized wastewater treatments, and which are exploring the efficacy of centralized WSP against the existing decentralized treatments.

Pesticides monitoring in surface water of a subsistence agricultural catchment in Uganda using passive samplers

Pesticides are intensely used in the agricultural sector worldwide including smallholder farming. Poor pesticide use practices in this agronomic setting are well documented and may impair the quality of water resources. However, empirical data on pesticide occurrence in water bodies of tropical smallholder agriculture is scarce. Many available data are focusing on apolar organochlorine compounds which are globally banned. We address this gap by studying the occurrence of a broad range of more modern pesticides in an agricultural watershed in Uganda. During 2.5 months of the rainy season in 2017, three passive sampler systems were deployed at five locations in River Mayanja to collect 14 days of composite samples. Grab samples were taken from drinking water resources. In these samples, 27 compounds out of 265 organic pesticides including 60 transformation products were detected. In the drinking water resources, we detected eight pesticides and two insecticide transformation products in low concentrations between 1 and 50 ng/L. Also, in the small streams and open fetch ponds, detected concentrations were generally low with a few exceptions for the herbicide 2,4-D and the fungicide carbendazim exceeding 1 ug/L. The widespread occurrence of chlorpyrifos posed the largest risk for macroinvertebrates. The extensive detection of this compound and its transformation product 3,4,5-trichloro-2-pyridinol was unexpected and called for a better understanding of the use and fate of this pesticide.

Combined toxicity of chlorpyrifos, abamectin, imidacloprid, and acetamiprid on earthworms (Eisenia fetida)

Mixed pesticides have been broadly used in agriculture. However, assessing the combined effects of pesticides in the environment is essential for potential risk assessment, though the task is far from complete. Median lethal concentrations of pesticides as well as acetylcholinesterase (AChE) levels and cellulose activities were measured in earthworms (Eisenia fetida) individually and jointly exposed to pesticides imidacloprid (IMI), acetamiprid (ACE), chlorpyrifos (CRF), and abamectin (ABM)). A 3:1 mixture of CRF and IMI had additive effects, while a 3:1 mixture of CRF and ACE had synergic effects. The joint effects of ABM with IMI or with ACE were synergistic. As CRF concentration increased, AChE activities were significantly decreased. For high concentrations of IMI, AChE activities under combined CRF and IMI applications were significantly inhibited following increased exposure time. Moreover, the cellulase activities under combined applications of CRF with IMI or with ACE had similar effects. This study provides basic data for scientifically evaluating the environmental risk and safety of combined uses of pesticides.

Screening and prioritizing substances in groundwater in the Beijing-Tianjin-Hebei region of the North China Plain based on exposure and hazard assessments

Screening and prioritizing hazardous substances in groundwater is crucial to monitor and control groundwater quality. Total of 283 substances were determined in 213 groundwater samples from the Beijing-Tianjin-Hebei region during 2019-2020. 184 substances were screened as candidates. 22 prioritizing indicators were evaluated and scored for the candidates to reflect their occurrence, mobility, persistence, bioaccumulation, acute and chronic ecotoxicities with different trophic levels, and long-term human health effects. Multi-attribute decision-making technologies were applied to prioritize these candidates, including analytic hierarchy process (AHP), TOPSIS and VIKOR. Greater weightings in AHP were assigned to attributes of occurrence and acute toxicity by experts' judgment. Hierarchical cluster analysis and principal component analysis were used to transform initial matrix with the 22 indicators into an orthogonalized matrix with 6 principal components, which represented general toxicity to aquatic organism and mammal, bioaccumulation, carcinogenicity & mutagenicity, persistence, and teratogenicity & endocrine, respectively. VIKOR and TOPSIS results were similar, but different from the AHP ranking. Two filter criteria harmonized their difference. Twenty-three substances were proposed as the priority substance with high hazard and potential exposure, and nitrate-nitrogen and ammonia-nitrogen were selected as additional priority substance frequently and extensively exceeding official groundwater quality standard on the regional scale.

A Review on Prediction Models for Pesticide Use, Transmission, and Its Impacts

The lure of increased productivity and crop yield has caused the imprudent use of pesticides in great quantity that has unfavorably affected environmental health. Pesticides are chemicals intended for avoiding, eliminating, and mitigating any pests that affect the crop. Lack of awareness, improper management, and negligent disposal of pesticide containers have led to the permeation of pesticide residues into the food chain and other environmental pathways, leading to environmental degradation. Sufficient steps must be undertaken at various levels to monitor and ensure judicious use of pesticides. Development of prediction models for optimum use of pesticides, pesticide management, and their impact would be of great help in monitoring and controlling the ill effects of excessive use of pesticides. This paper aims to present an exhaustive review of the prediction models developed and modeling strategies used to optimize the use of pesticides.