Next Article in Journal
Network Analysis of Outcome-Based Education Curriculum System: A Case Study of Environmental Design Programs in Medium-Sized Cities
Previous Article in Journal
Preliminary Research on the Efficacy of Selected Herbicides Approved for Use in Sustainable Agriculture Using Spring Cereals as an Example
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 17
Issue 15
10.3390/su17157088
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Spatial and Temporal Distribution of Conversational and Emerging Pollutants in Fecal Sludge from Rural Toilets, China

by
Lin Lin
1,2,
Yilin Shen
1,
Guoji Ding
1,
Shakib Alghashm
1,
Seinn Lei Aye
2 and
Xiaowei Li
1,*
1
School of Environmental and Chemical Engineering, Organic Compound Pollution Control Engineering, Ministry of Education, Shanghai University, Shanghai 200444, China
2
Department of Industrial Chemistry, University of Yangon, Yangon 11000, Myanmar
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(15), 7088; https://doi.org/10.3390/su17157088
Submission received: 22 June 2025 / Revised: 26 July 2025 / Accepted: 29 July 2025 / Published: 5 August 2025
(This article belongs to the Special Issue Biological Treatment for Sustainable Waste Management and Green Environment)
Browse Figures
Versions Notes

Abstract

Effective management of fecal pollutants in rural sanitation is crucial for environmental health and public safety, especially in developing regions. In this study, temporal and regional variations in nutrient elements, heavy metals, pathogenic microorganisms (PMs), and antibiotic resistance genes (ARGs) of fecal samples from rural toilets in China were investigated. The moisture contents of the fecal samples average 92.7%, decreasing seasonally from 97.4% in summer to 90.6% in winter. The samples’ pH values range from 6.5 to 7.5, with a slight decrease in winter (6.8), while their electrical conductivity varies from 128.1 to 2150 μs/cm, influenced by regional diets. Chromium (9.0–49.7 mg/kg) and copper (31.9–784.4 mg/kg) levels vary regionally, with higher concentrations in Anhui and Guangxi Provinces due to dietary and industrial factors. Zinc contents range from 108.5 to 1648.9 mg/kg, with higher levels in autumn and winter, resulting from agricultural practices and Zn-containing fungicides, posing potential health and phytotoxicity risks. Seasonal and regional variations in PMs and ARGs were observed. Guangxi Province shows the high PM diversity in summer samples, while Jiangsu Province exhibits the high ARGs types in autumn samples. These findings highlight the need for improved waste management and sanitation solutions in rural areas to mitigate environmental risks and protect public health. Continued research in these regions is essential to inform effective sanitation strategies.

Graphical Abstract

1. Introduction

Waste management and sanitation in rural regions are essential for maintaining environmental sustainability and protecting public health. The United Nations’ Sustainable Development Goal (SDG) 6.3 aims to provide safe and managed sanitation systems for all people by 2030 [1]. Inadequate waste management and sanitation infrastructure in rural regions can pollute the air, soil, and water, posing severe health risks to human beings and neighboring communities [2]. More than 1.8 million people die yearly from waterborne diseases such as cholera, dysentery, and typhoid, which are caused by pathogens such as Vibrio cholerae, Shigella spp., and Salmonella in untreated human waste [3,4,5]. Infectious diseases such as cholera, dysentery, and typhoid can spread because of the untreated disposal of human waste and some organic waste [6]. These diseases are particularly prevalent in areas with inadequate sanitation systems [7].
The contamination of groundwater and surface water by fecal matter poses dual risks to residents of rural areas who rely on untreated water sources for drinking and hygiene practices [8]. Agricultural runoff and livestock waste release more fecal pathogens into water systems, disrupting aquatic ecosystems and endangering biodiversity [9]. Pathogen survival rates vary with seasonal temperature and precipitation changes, thus increasing pathogen transmission during damp seas [10,11]. Developing intervention methods for global sanitation objectives, including SDG 6, depends on complete comprehension of fecal pollutant spatial and temporal patterns. This study investigates the factors influencing the spatial and temporal distributions of fecal pollutants in rural sanitation systems, offering critical insights for developing more effective and region-specific sanitation strategies. By analyzing these distribution patterns, the study contributes to a deep understanding of the dynamics of fecal contamination in rural environments, which is essential for addressing public health and environmental risks associated with inadequate sanitation.
However, particularly in developing countries like China, most manure is discarded as waste rather than a valuable resource [12]. The main nutrients that cause water eutrophication are nitrogen and phosphorus. When feces are discharged into water without treatment, high levels of these nutrients promote excessive growth of algae and aquatic plants, leading to oxygen depletion and negatively impacting aquatic ecosystems. Meanwhile, the release of harmful gases containing odor components such as ammonia, hydrogen sulfide, and mercaptan further contributes to environmental pollution and inconveniences surrounding residents’ daily lives [13]. Seasonal variations in nutrient content, including total nitrogen (TN), total phosphorus (TP), total potassium (TK), and organic matter (OM), significantly impact the characteristics of rural toilet feces across different regions of China. Tong et al. [14] found that TN levels fluctuate throughout the year, influenced by dietary habits and climatic conditions. Understanding these variations is essential for optimizing resource utilization and enhancing waste management practices to mitigate environmental risks associated with nutrient discharge [15]. Additionally, heavy metals in feces can enter environmental water bodies and subsequently accumulate in the human body through the food chain, resulting in diseases like kidney damage and bone pain.
Human and animal excrement produce fecal pollutants, including numerous organic and inorganic chemicals, creating extensive health hazards and environmental challenges. Heavy metals; pathogenic microorganisms (PMs); and emerging contaminants such as pharmaceuticals, nutrients, and personal care products are common pollutants in these environments [16,17]. Gao et al. [18] reported that environmental contamination from fecal matter remains severe due to insufficient rural sanitation facilities. Guo et al. [19] investigated fecal pollution patterns in China, a process which requires detailed research due to worsening conditions during urbanization and industrialization.
The characteristics of fecal pollutants in rural toilets have exposed significant differences in these contaminants between different geographic regions and seasons in China [20]. Physical and chemical analyses showed that feces’ characteristics, consisting of pH values, moisture content (MC), and nutritional components, change substantially through variations in local environments and sanitation practices [21,22]. Heavy metals such as Cr, Cu, and Zn must be measured in the feces because they help identify potential threats from soil and water contamination [23].
The PM in the feces represents a significant health threat, and if the management of rural sanitation facilities is improper, these pathogens can become lethal. Pathogens present in fecal samples, such as E. coli, Salmonella, and enteric viruses, indicate poor waste-disposal compliance and their ability to spread diseases widely [24]. The environmental pathogens identified by frequency and geographic location are necessary for adequate community health protection. Mishra et al. [25] showed that emerging pollutants among pharmaceuticals and personal care products continue to increase in human fecal samples, generating environmental concerns and health risks. In this study, the presence of antibiotic resistance genes (ARGs) in fecal waste proves highly concerning because it increases the severity of the public health crisis.
Despite increasing recognition of the rural sanitation’s significance, substantial gaps remain in our understanding of the spatial and temporal dynamics of fecal pollutants across diverse regions of China. While studies by Zhang et al. [26] have contributed valuable insights into localized contaminants or specific geographic contexts, their scope often lacks a holistic, nationwide perspective that accounts for regional and seasonal variations in fecal pollution. This narrow focus has constrained the formulation of tailored sanitation interventions, leaving critical questions about broader contamination patterns—and their implications for public health and environmental policy—largely unanswered.
This study adopted a comprehensive, multi-parameter approach to analyze fecal pollutants, integrating microbiological, heavy metal, and nutrient data to evaluate their associated health and environmental risks in rural sanitation systems. Through a systematic investigation of pollution characteristics in rural toilet feces across diverse regions and seasons in China, this study pursued three key objectives: (1) to quantify the spatiotemporal distribution of heavy metals (Cr, Cu, and Zn), PMs, and emerging contaminants (ARGs); (2) to assess the associated health and environmental risks across two critical phases, i.e., toilet containment and agricultural reuse; and (3) to provide science-based recommendations for safe resource utilization, supporting China’s ‘toilet revolution’ policy framework. By establishing region-specific contamination profiles, this study provides critical insights to guide the development of tailored treatment strategies, ensuring a balance between ecological safety and sustainable rural development.

2. Materials and Methods

2.1. Sample Collecting and Locations of Study Area

The fecal materials used in this study were collected from rural toilets in three provinces in China (Figure 1). During the sampling process, samples were taken from the thicker bottom layer of the toilets to ensure representative collection. The samples were filtered to remove impurities, mixed evenly to ensure consistency, and then stored in plastic buckets at 4 °C [22]. As shown in Table 1, nine samples were collected: three samples from Wuhu City, Anhui Province (spring 2020 ①, summer 2019 ②, and autumn 2019 ③); one sample from Fuyang City, Anhui Province (winter 2020 ④); two samples from Nanning City, Guangxi Province (summer 2020 ⑤ and winter 2019 ⑥); and three samples from Nanjing City, Jiangsu Province (summer 2020 ⑦, autumn 2020 ⑧ in 2020, and winter 2020 ⑨). Each sample was analyzed in triplicate to ensure the reliability and reproducibility of the results.

2.2. Physicochemical Analysis

MC was determined by drying the compost sample at 105 °C for 24 h, while the organic matter (OM) was quantified by measuring mass loss upon ignition at 550 °C for 4 h in a muffle furnace. The pH value and electrical conductivity (EC) were measured using the appropriate pH/EC meter (Thermo Scientific, Waltham, MA, USA). TN, TP, and TK were estimated using the samples that were freeze-dried, ground in a mortar, and filtered through a 200-mesh sieve. The TN was determined using an element analyzer, while TP was measured using molybdenum antimony resistance spectrophotometry. TK and Ca analyses were conducted using an atomic absorption spectrophotometer after digestion with a concentrated sulfuric acid solution with hydrogen peroxide (H2O2) [27].

2.3. Determination of Heavy Metals in Fecal Matter

Heavy metal (Cr, Cu, and Zn) contents were analyzed using freeze-dried, ground, and filtered samples based on the US-EPA Method 3051 [28]. Each sample of 0.10 ± 0.01 g was digested in a mixture consisting of 8 mL of 60% nitric acid, 1 mL of 50% hydrofluoric acid, and 1 mL of 30% H2O2, using a microwave digestion apparatus. The digestion process took place at 180 ± 5 °C for 20 min. After digestion, the samples were diluted to a volume of 50 mL with deionized water and stored in a freezer at a temperature below −4 °C [28]. Subsequently, the concentrations of the heavy metals were determined using inductively coupled plasma–optical emission spectrometry (ICP-OES), utilizing an Optima 8000 instrument from PerkinElmer, Waltham, MA, USA [7].

2.4. Analysis of Pathogenic Microorganism (PM) and Antibiotic Resistance Genes (ARGs)

PMs and ARGs were analyzed using the samples collected seasonally from four locations in China: winter sample from Fuyang City, Anhui Province; spring sample from Wuhu City, Anhui Province; summer sample from Nanning City, Guangxi Province; and autumn sample from Nanjing City, Jiangsu Province. The samples were not mixed between different seasons or regions, and each was processed and analyzed separately to accurately reflect the differences among seasons.
The PMs and ARGs were analyzed using a complete molecular testing method through Silva and an antibiotic resistance gene database (ARDB) [29,30]. DNA extraction for fecal samples employed the E.Z.N.A.® soil kit produced by Omega Bio-tek from Norcross, GA, USA. DNA quality was checked by 1% agarose gel electrophoresis, while DNA concentration and purity values were assessed through Nano Drop 2000 spectrophotometer analysis. The primer pair 338F and 806R amplified the V3-V4 region of the 16S rRNA gene within PCR cycles operated at 95 °C for 3 min and then ran 27 rounds at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s before ending with a 72 °C extension period of 10 min. PCR product purification used the AxyPrep DNA Gel Extraction Kit, while quantification occurred through QuantiFluor™-ST (Promega, Madison, WI, USA). All sequencing performed on the Illumina MiSeq system required Trimmomatic (v0.39) and FLASH software (v1.2.11) to monitor quality control. The RDP classifier analyzed sequences processed through UPARSE for cluster generation by referring to the Silva database for species annotation. The analysis of ARGs was conducted using the BLASTP algorithm, which compared the non-redundant gene set with the ARDB to measure resistance function abundances [29,30].

3. Results and Discussions

3.1. Physicochemical Characteristics of Rural Toilet Feces

The MC of feces in rural toilets fluctuates roughly from 85.11% to 97.25%, with an average MC of 92.70%, as shown in Figure 2a. This high moisture is attributed to the failure of effective separation of separation between feces and urine in conventional dry toilets, leading to challenges in subsequent reclamation processes. The average fecal MC in summer, autumn, and winter was 97.40%, 92.80%, and 90.60%, respectively, indicating a gradual decline trend from summer to winter. The result may be related to the frequency of human activities. As the weather changes from hot to cold (Table 1), people’s activities and sweating gradually decrease; consequently, the water intake and excretion in the human body also reduce, leading to a reduction in the proportion of urine in rural toilets and a decrease in fecal MC. Meanwhile, average fecal MC in Anhui Province (about 91%) is lower than that in Guangxi Province (about 93%). The possible reason is that Guangxi Province is much warmer than Anhui Province. In warmer areas, human activities, as well as water intake and excretion levels, are higher than in colder regions, resulting in higher fecal MC.
The pH of fecal matter in rural toilets fluctuates roughly in the range of 6.5–7.5, with an average pH of 7.1 (Figure 2b). The pH of rural dry toilet feces remains within the neutral range. A suitable pH facilitates the subsequent resource recovery from feces. The average pH of feces in summer, autumn, and winter was 7.2, 7.1, and 6.8, respectively, with slight variations in pH, implying a slight downward trend from summer to winter. Meanwhile, the average pH of rural toilet feces in Guangxi Province and Jiangsu Province are about 7.4 and 6.9, respectively. The regional differences in the rural toilet feces may be related to dietary habits in different places, which requires further study.
EC values are varied within the range of 128.1 to 2150 μs/cm, with an average of 836 μs/cm (Figure 2c). The average fecal EC values in summer, autumn, and winter are 795 μs/cm, 724 μs/cm, and 514 μs/cm, respectively, indicating a decreasing trend from summer to winter. The result may be related to food preferences in different seasons. Humans eat more foods with higher oil content in winter, and they consume more electrolyte-containing foods due to large amounts of sweat in the summer. The EC of feces from Guangxi Province is stable at about 1000 μs/cm, which is consistent with the speculation that people eat more electrolyte-supplementing foods during hot weather. In addition, Guangxi people prefer fruits and vegetables that are pickled, well-seasoned, and rich in electrolytes.

3.2. Nutrient Elements and Calcium (Ca)

3.2.1. Nutrient Elements

TN ranges from 19.28 g/kg to 49.85 g/kg, with an average of 32.86 g/kg (Figure 3a), indicating significant potential for resource utilization. The TN of feces fluctuates from summer to winter. The average TN in summer, autumn, and winter was 32.81, 27.72, and 40.87 g/kg, respectively. In general, there was no significant regional difference in the TN content.
TP content of rural feces varies with season, with an average value of 3.08 g/kg. The average TP value of feces in summer, autumn, and winter was 2.80, 3.60, and 3.80 g/kg, respectively, implying an increasing trend from summer to winter (Figure 3b). Like TN, there are no significant regional differences in the TP content of feces in rural toilets based on the results of this experiment.
TK ranges from 3.17 g/kg to 34.40 g/kg, with an average value of 11.14 g/kg (Figure 3c). The potassium content is still relatively considerable, which has good utilization value for subsequent resource treatment. The average TK values of feces in summer, autumn, and winter were 7.35, 3.15, and 19.01 g/kg, respectively, implying a first decreasing and then increasing trend. The average TK of rural toilet feces in Anhui Province (16.55 g/kg) is higher than that in Guangxi Province (3.24 g/kg), indicating a significant regional distribution difference in TP.
The OM content in rural toilet feces ranges from 40.40% to 74.95%, averaging 58.20% (Figure 3d). This content is crucial for composting, as it fulfills the microbial requirements when mixed with bulking agents. The average OM content decreases from 65.26% in summer to 50.70% in winter, reflecting seasonal variations, possibly due to the variation in the temperature, according to Lepane et al. [31]. Meanwhile, the average OM content of feces from Guangxi Province (70.20%) is higher than that from Anhui Province (56.43%) and Jiangsu Province (52.56%). The average temperature in Guangxi Province was also higher than in these two provinces (Table 1). This phenomenon confirms relatively high OM content of rural toilet feces in regions and seasons with high temperatures.

3.2.2. Calcium (Ca)

Ca content in rural toilet feces ranges from 12.78 to 120.85 g/kg, with an average value of 45.01 g/kg (Figure 4). The Ca in the feces is beneficial to agricultural soils. It can supply Ca to plants and regulate the pH level of soil [32]. In addition, Ca application can modify soil chemistry to reduce the concentration of soluble heavy metal species while simultaneously decreasing plant accumulation of these toxic elements [33]. Thus, the Ca generally has a good resource value. The average Ca contents of the summer, autumn, and winter samples are 47.40, 82.98, and 25.74 g/kg, respectively; as can be seen, the content was exceptionally high in the autumn sample. The average fecal calcium (Ca) content in rural toilets varied geographically. Compared with other provinces, the higher Ca content in Jiangsu Province may have resulted from the more developed economy and higher consumption of Ca-rich foods or supplements.

3.3. Heavy Metal Elements

3.3.1. Chromium (Cr)

As shown in Figure 5, the Cr content in the fecal samples from rural toilets ranges from 9.0 to 49.7 mg/kg, exhibiting a wide range of variation. The average Cr content is 27.38 mg/kg, comfortably below the legislative limit of approximately 60 mg/kg, indicating a low risk associated with this metal [34]. Cr can affect soil physicochemical properties and microbial community diversity [35]. High concentrations of Cr inhibit the growth of microorganisms and reduced enzyme activity. Meanwhile, Cr (VI) can enter the human body through the food chain, leading to adverse consequences such as cancer, deformities, and genetic mutations [36]. Therefore, harmless treatment is required for rural toilet feces before resource utilization. This is crucial not only for mitigating health risks associated with Cr exposure from untreated fecal matter but also for ensuring that any agricultural reuse of this material is safe and sustainable.
The average Cr content in summer, autumn, and winter was 27.57 mg/kg, 27.55 mg/kg, and 25.74 mg/kg, respectively, implying that Cr content in feces exhibited fluctuations throughout the seasons, and no clear seasonal variation was observed. Meanwhile, the average Cr content in Jiangsu Province is much lower than in the other two provinces. This result indicates that the food chain within residents’ diet at this experimental site in Nanjing, Jiangsu Province, has relatively low Cr contamination. These findings highlight the dominant role of region-specific dietary and industrial factors over seasonal variations in Cr content. This was supported by the significant inter-regional variation, where average Cr content in Anhui Province (31.88 mg/kg) substantially exceeds that in Jiangsu (14.7 mg/kg). The relatively stable Cr levels across seasons suggest (1) potential buffering effects from the complex interaction between human excretion patterns and environmental conditions; and (2) possible bioaccumulation in human tissues prior to fecal excretion, which may attenuate immediate seasonal responses. These observations corroborate previous findings by Alam [37], who reported consistently elevated fecal Cr concentrations (9.8–16.9 mg/kg) across all seasons, without demonstrating significant seasonal periodicity, thus further supporting the hypothesis that Cr excretion exhibits annual fluctuation rather than following predictable seasonal patterns.

3.3.2. Copper (Cu)

The Cu contents in fecal samples from rural toilets range from 31.9 to 784.4 mg/kg, showing significant variations (Figure 6). The average Cu content in rural toilets is 234.4 mg/kg, exceeding the legislative limits of 200 mg/kg and suggesting potential toxicity risks for agricultural applications [38]. Cu is an essential trace element in living organisms and a component of many cell metalloenzymes and proteins [39,40]. However, when the Cu content in the soil exceeds a certain threshold, it puts toxic effects on soil organisms and causes harmful and irreversible impacts on the soil function and quality [41]. Soil microorganisms are more susceptible than soil animals and plants to these effects, as Cu can affect their abundance, community structure, and function, leading to declines in soil quality and ecological disruption [42]. In addition, Cu reduces the compressive strength of soil by forming a soft body with a weak cementing ability that accelerates soil hardening and damages its structure [43].
The average Cu content in summer, autumn, and winter was 123.1 mg/kg, 402.85 mg/kg, and 300.5 mg/kg, respectively, implying that the Cu content in feces tends to increase from summer to winter. The average Cu content in rural toilets in Anhui Province is 237 mg/kg, while in Guangxi Province and Jiangsu Province, the average contents are about 467.2 mg/kg and 75.3 mg/kg, respectively. The Cu content of the fecal sample in Jiangsu Province is much lower than that in the other two provinces. The result implies that the food chain within residents’ diet in Jiangsu Province is lightly contaminated by Cu. The variations in Cu content and its health risks emphasize the need for treating fecal waste from rural toilets to prevent Cu exposure and ensure safe use as fertilizer, supporting sustainable agriculture. The previously established tolerance limit for Cu in foods, defined as 10 mg·kg−1, is applied as the regulated contamination level for Cu in agricultural products according to the standard GB15199-94 [44]. This criterion is a benchmark for assessing Cu levels in food safety and farming practices.

3.3.3. Zinc (Zn)

The Zn content in the fecal matter from rural toilets ranges from 109.5 mg/kg to 1648.9 mg/kg (Figure 7). The average Zn content is 764.6 mg/kg, surpassing the legislative limits of 300 mg/kg [45]. Zn is also a necessary trace element for the growth and development of plants and animals, and it has a specific promotional effect on plant growth under appropriate concentrations [46,47]. However, when the soil contains an excessive concentration of Zn, it can become toxic to plants. Additionally, Zn accumulates, migrates, and transfers through the food chain, posing a significant threat to human health [48]. Therefore, it is essential to treat rural toilet feces containing Zn harmlessly before discharge or reuse.
The average Zn content in feces during summer, autumn, and winter was 797.4 mg/kg, 966.2 mg/kg, and 816.2 mg/kg, respectively, implying a slightly increasing tendency from summer to winter. The Zn content of the rural toilet feces from Jiangsu Province remains relatively stable, with little change throughout the season. However, a considerable increase in Zn content is observed in Anhui Province and Guangxi Province from summer to winter.
The average Zn content of the rural toilet feces in Anhui Province is 700.18 mg/kg, which is lower than that in Guangxi Province (1490.15 mg/kg), but higher than that in Jiangsu Province (367.20 mg/kg). Residents in Guangxi should be cautious about potential excessive Zn intake through their daily food. Regional patterns of Zn contamination in soils are influenced by both natural and anthropogenic factors, resulting in significant differences between urbanized and agricultural regions. Stable and low Zn levels in Jiangsu Province are attributed to limited agricultural activity and minimal application of Zn-rich fertilizers or pesticides, leading to consistent baseline excretion and minimal seasonal fluctuations. Anhui and Guangxi Provinces exhibit pronounced seasonal increases in Zn concentrations, primarily associated with agricultural practices such as winter manure application and Zn-containing fungicides, which introduce substantial Zn loads into the soil during specific periods. National-scale studies indicate that Zn accumulation in Chinese agricultural soils generally exceeds global averages, with hotspots of contamination closely linked to anthropogenic activities, including intensive farming, mining, and industrial emissions, particularly in orchards and paddy fields [49,50].
Zn is an essential soil component for plant growth, influencing various metabolic pathways. However, excessive Zn levels can harm plants, leading to reduced growth, impaired photosynthesis and respiration, nutritional imbalances, and increased reactive oxygen species. Sources of Zn in soils include rock weathering, forest fires, volcanic activity, mining, smelting, manure, sewage sludge, and fertilizers. The balance between Zn’s essentiality and toxicity has raised concerns among scientists regarding its impact on plants and agricultural sustainability. The study by Kaur [51] elucidates the physiological and biochemical disturbances induced by elevated zinc (Zn) concentrations in plants, detailing its uptake dynamics, transport mechanisms, and homeostatic regulation. Notably, 400 mg/kg is identified as the critical toxicity threshold for Zn in plant systems. Zn levels in summer and autumn samples from Anhui Province, and summer and winter samples from Guangxi Province exceed this threshold, indicating a high risk of Zn-induced phytotoxicity. The values in spring and winter samples from Anhui Province and autumn samples from Jiangsu Province remain lower than the toxic threshold, while the summer and winter samples in Jiangsu Province are near the toxic threshold, suggesting potential sub-toxic stress. These results imply that Zn contents of the fecal samples are influenced by geographic location and seasonal factors, with elevated concentrations primarily occurring in warmer periods.
This study provides valuable insights into the spatial and temporal distribution of fecal contaminants, enabling the identification of vital activities and sources of contamination when correlated with environmental and demographic data [52]. Potential valorization routes for fecal material, such as biogas production or nutrient recovery, must be approached with caution, particularly in regions where heavy metal content is high [53]. In such areas, composting and using stabilized fecal material as organic amendments should be avoided to prevent the introduction of heavy metals into agricultural soils, which can adversely affect soil health and crop safety [54]. Both heavy metals and nutrients play a critical role in shaping the composition and functionality of microbial communities, often leading to an increased prevalence of resistant and potentially pathogenic bacteria [55].

3.4. Microbiological Contaminants

3.4.1. Pathogenic Microorganisms (PMs)

The top 50 PMs in taxonomic abundance at the genus level are shown in Figure 8, including Salmonella, Chlamydia, mycoplasma, Spirochaeta, fecal Escherichia coli, Bacillus anthracis, and Mycobacterium tuberculosis. The PMs of the winter sample from Anhui Province are less abundant than those from the other three seasons. This aspect may be related to decreased microbial activity during winter, when many non-hardy organisms cannot survive. The abundance and species of microorganisms in the spring samples from Anhui Province are similar to that in the autumn samples from Jiangsu Province, due to the climate similarity between spring and autumn.
As shown in Figure 9, the winter samples from Anhui Province have the lowest number of PM species among these samples, while the other season samples have similar species richness of PMs. The summer sample from Guangxi Province contains 115 unique species of PM, showing considerable differences from other samples. The sample from Anhui Province only had 24 unique PM species. These results are primarily driven by the following factors: (1) Guangxi Province has a higher temperature than Anhui Province (Table 1), thus strongly influencing microbial survival and proliferation; and (2) Guangxi Province is near the South China Sea, and people have higher consumption of fresh aquatic products than people in Anhui Province do, thus possibly introducing additional aquatic-borne pathogens. Meanwhile, the number of coexisting PM species across all four samples is 524. The results imply the presence of a lot of PMs in rural toilet feces, which should not be ignored in subsequent resource treatment. The present standard of fecal safety mentions only two pathogenic bacteria: fecal coliform and Salmonella, which may be not enough and necessary to pay attention to more fecal PMs.

3.4.2. ARGs (Emerging Biological Pollutants)

As shown in Figure 10, the autumn samples from Jiangsu Province have the highest number of ARG types, while the summer samples from Guangxi Province have the fewest among the samples. Huang et al. [56] and Wang [57] have shown that ARG distribution is influenced by geographic proximity, shared medical practices, and drug preferences. Pei et al. [58] and Zhao et al. [59] found that urban areas accumulate more ARGs than rural zones due to higher antibiotic usage, supporting the result based on the Jiangsu samples. Meanwhile, the ARG types overlap with 115 common genes between Anhui and Jiangsu Provinces, which is higher than those between Anhui and Guangxi Provinces (60). It is well-known that Anhui Province is near to Jiangsu Province (Figure 1). Cedeño-Muñoz et al. [60] determined that adjacent provinces share many ARGs, implying shared resistance risks and, thus, highlighting the need for regional antibiotic surveillance.
These studies highlight the persistence and spread of ARGs and other contaminants in various environmental settings. An et al. [61] observed significant reductions in ARG abundance during wastewater treatment, but they noted that some ARGs persisted and are even enriched in effluents. Hubeny et al. [62] determined that industrialized areas have higher concentrations of heavy metals and antibiotics in wastewater, correlated with increased ARG levels. These findings underscore the challenges in mitigating health risks associated with ARGs and other contaminants in sanitation systems and the broader environment. Li et al. [63] also found high ARG residues in human feces after rural toilet treatment in China, with toilet types and nitrogen compounds influencing ARG profiles. This study emphasizes the inadequacy of current toilet systems in mitigating health risks, as ARGs persist post-treatment, and heavy metals and PMs remain elevated, especially in Guangxi and Anhui Provinces. While Li identified toilet type, TN, and NH3-N as ARG drivers, this study points to external factors (e.g., climate and local industry) affecting metal and PM variability. Both studies indicate persistent fecal contamination risks, necessitating improved treatment strategies for agricultural reuse and public health. Regions with high metal concentrations (e.g., Guangxi Province for Cu and Zn) may also face elevated ARG and PM exposure, compounding disease risks. Future policies must address these interconnected hazards through standardized monitoring and advanced sanitation technologies.

3.5. The Limitation of Study

The sampling did not fully represent all rural sanitation contexts in China, as regional practices and conditions vary. More samples should be collected from more provinces in future studies. Differences in toilet designs can influence the characteristics of fecal matter. Some toilets mix feces with urine or kitchen waste, affecting MC and nutrient levels. Standardizing sampling methods would help address this variability. Although we sampled across different seasons, the timing may not capture all seasonal variations in fecal composition. More frequent sampling could provide a clearer picture of temporal changes. The microbial assessment focused on specific pathogens and ARGs but did not cover the full microbial diversity in fecal matter. A broader analysis could yield deeper insights into health risks. We targeted specific heavy metals, leaving out other contaminants. Future research should include more pollutants, such as microplastics, pharmaceuticals, and personal care products (PPCPs), for a comprehensive understanding of risks associated with rural sanitation.

4. Conclusions

This study reveals significant spatial and temporal variations in nutrient elements, heavy metal concentrations (Cr, Cu, and Zn), and microbiological contaminants (PMs and ARGs) in rural toilet feces across China, with critical implications for environmental and public health. The concentrations of fecal pollutants exhibit significant regional variations across China, with Guangxi Province demonstrating substantially higher heavy metal levels compared to the lower concentrations observed in Jiangsu Province. Seasonal fluctuations in pollutant levels suggest that climate plays a significant role in microbial dynamics, with lower microbial contaminants in the winter. To effectively mitigate these risks of fecal pollutants, it is imperative to implement region-specific sanitation strategies that incorporate microbial inactivation processes and advanced heavy metal removal technologies. It is crucial to establish a comprehensive monitoring system for tracking heavy metal concentrations and microbial contaminants in rural toilet feces for evidence-based policymaking and safeguarding public health. Furthermore, policy frameworks should be tailored to accommodate local environmental characteristics while promoting sustainable agricultural practices. Collectively, these measures—including optimized waste management systems, State-of-the-Art treatment technologies, and rigorous pollution monitoring—will substantially reduce the public health hazards associated with rural fecal waste in China.

Author Contributions

Conceptualization, L.L., Y.S., G.D., S.A. and X.L.; data curation, Y.S.; formal analysis, L.L. and G.D.; investigation, L.L. and Y.S.; methodology, L.L., Y.S. and X.L.; project administration, X.L.; resources, X.L.; software, Y.S., G.D. and S.A.; supervision, X.L.; validation, L.L., G.D., S.A. and X.L.; visualization, S.L.A.; writing—original draft, L.L. and Y.S.; writing—review and editing, L.L., S.L.A. and X.L. All authors have read and agreed to the published version of the manuscript.

Funding

The authors are grateful for the support from the National Key R&D Program of China (2023YFC3905603), the National Natural Scientific Foundation of China (52070126), and the Shanghai Committee of Science and Technology (22WZ2505300 and 19DZ1204702).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available upon request from the corresponding author.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.

References

  1. United Nations Human Settlements Programme (UN-Habitat); World Health Organization (WHO). Progress on the Proportion of Domestic and Industrial Wastewater Flows Safely Treated—Mid-Term Status of SDG Indicator 6.3.1 and Acceleration Needs, with a Special Focus on Climate Change, Wastewater Reuse and Health; United Nations Human Settlements Programme (UN-Habitat): Nairobi, Kenya; World Health Organization (WHO): Geneva, Switzerland, 2024. [Google Scholar]
  2. Vinti, G.; Vaccari, M. Solid waste management in rural communities of developing countries: An overview of challenges and opportunities. Clean Technol. 2022, 4, 1138–1151. [Google Scholar] [CrossRef]
  3. Kour, D.; Khan, S.; Ramniwas, S.; Kumar, S.; Rai, A.; Rustagi, S.; Chaubey, K.; Singh, S.; Ahluwalia, A. Beneficial fungal communities for sustainable development: Present scenario and future challenges. J. Appl. Biol. Biotechnol. 2024, 12, 1–9. [Google Scholar] [CrossRef]
  4. Shayo, G.M.; Elimbinzi, E.; Shao, G.N.; Fabian, C. Severity of waterborne diseases in developing countries and the effectiveness of ceramic filters for improving water quality. Bull. Nat. Res. Centre 2023, 47, 113. [Google Scholar] [CrossRef]
  5. Dila, D.; Corsi, S.; Lenaker, P.; Baldwin, A.; Bootsma, M.; McLellan, S. Patterns of host-associated fecal indicators driven by hydrology, precipitation, and land use attributes in great lakes watersheds. Environ. Sci. Technol. 2018, 52, 11500–11509. [Google Scholar] [CrossRef]
  6. Sindua, N.J.; Kaihatu, J.E. Community respond to waste treatment base on 3R (reduce, reuse and recycle) in the settlement environment of moronge village, moronge district, Talaud Islam regency. In E3S Web of Conferences, Proceedings of the International Conference on Science and Technology (ICST 2021), Ternate, Indonesia, 27–28 October 2021; EDP Sciences: Paris, France, 2021; Volume 328, p. 08019. [Google Scholar] [CrossRef]
  7. Custodio, M.; Orellana, E.; Peñaloza, R.; De la Cruz Solano, H.; Bulege Gutiérrez, W. Heavy metal accumulation in sediment and removal efficiency in the stabilization ponds with the hydrocotyle ranunculoides filter. J. Ecol. Eng. 2020, 21, 72–79. [Google Scholar] [CrossRef]
  8. Atkinson, K.; Journal, T.I. An epidemiological survey of non-municipal drinking water supplies among rural communities in the Blue and John Crow Mountain ranges. Texila Int. J. Public Health 2022, 10, 22. [Google Scholar] [CrossRef]
  9. Albou, E.; Abdellaoui, M.; Abdaoui, A.; Ait Boughrous, A. Agricultural Practices and their Impact on Aquatic Ecosystems—A Mini-Review. Ecol. Eng. Environ. Technol. 2024, 25, 321–331. [Google Scholar] [CrossRef]
  10. Cissé, G. Foodborne and waterborne diseases under climate change in low- and middle-income countries: Further efforts needed for reducing environmental health exposure risks. Acta Trop. 2019, 194, 181–188. [Google Scholar] [CrossRef]
  11. Genter, F.; Willetts, J.; Foster, T. Faecal contamination of groundwater self-supply in low- and middle income countries: Systematic review and meta-analysis. Water Res. 2021, 201, 117350. [Google Scholar] [CrossRef]
  12. Nandi, A.; Megiddo, I.; Ashok, A.; Verma, A.; Laxminarayan, R. Reduced burden of childhood diarrheal diseases through increased access to water and sanitation in India: A modeling analysis. Soc. Sci. Med. 2017, 180, 181–192. [Google Scholar] [CrossRef]
  13. Shang, X.; Huang, H.; Mei, K.; Xia, F.; Chen, Z.; Yang, Y.; Dahlgren, R.A.; Zhang, M.; Ji, X. Riverine nitrate source apportionment using dual stable isotopes in a drinking water source watershed of southeast China. Sci. Total Environ. 2020, 724, 137975. [Google Scholar] [CrossRef] [PubMed]
  14. Tong, Y.; Li, J.; Qi, M.; Zhang, X.; Wang, M.; Liu, X.; Zhang, W.; Wang, X.; Lu, Y.; Lin, Y. Impacts of water residence time on nitrogen budget of lakes and reservoirs. Sci. Total Environ. 2019, 646, 75–83. [Google Scholar] [CrossRef] [PubMed]
  15. Al-Shammary, A.A.G.; Al-Shihmani, L.S.S.; Fernández-Gálvez, J.; Caballero-Calvo, A. Optimizing sustainable agriculture: A comprehensive review of agronomic practices and their impacts on soil attributes. J. Environ. Manag. 2024, 364, 121487. [Google Scholar] [CrossRef] [PubMed]
  16. Krishnani, K.K.; Boddu, V.M.; Singh, R.D.; Chakraborty, P.; Verma, A.K.; Brooks, L.; Pathak, H. Plants, animals, and fisheries waste-mediated bioremediation of contaminants of environmental and emerging concern (CEECs)—A circular bioresource utilization approach. Environ. Sci. Pollut. Res. 2023, 30, 84999–85045. [Google Scholar] [CrossRef]
  17. Anand, U.; Adelodun, B.; Cabreros, C.; Kumar, P.; Suresh, S.; Dey, A.; Ballesteros, F., Jr.; Bontempi, E. Occurrence, transformation, bioaccumulation, risk and analysis of pharmaceutical and personal care products from wastewater: A review. Environ. Chem. Lett. 2022, 20, 3883–3904. [Google Scholar] [CrossRef]
  18. Gao, Y.; Li, H.; Yang, B.; Wei, X.; Zhang, C.; Xu, Y.; Zheng, X. The preliminary evaluation of differential characteristics and factor evaluation of the microbial structure of rural household toilet excrement in China. Environ. Sci. Pollut. Res. 2021, 28, 43842–43852. [Google Scholar] [CrossRef]
  19. Guo, K.; Cao, Y.; Wang, Z.; Li, Z. Urban and industrial environmental pollution control in China: An analysis of capital input, efficiency and influencing factors. J. Environ. Manag. 2022, 316, 115198. [Google Scholar] [CrossRef]
  20. Fan, S.; Wang, H.; Ding, J.; Jia, Y.; Shen, Y.; Cheng, H.; Zhou, Y.; Li, D. Technical investigation and evaluation of rural sanitary dry toilets in cold and arid regions of China. Trans. Chin. Soc. Agric. Eng. Trans. CSAE 2022, 38, 225–233. [Google Scholar] [CrossRef]
  21. Li, X.; Wang, X.; Pan, X.; Zhu, P.; Zhang, Q.; Huang, X.; Deng, X.; Wang, Z.; Ding, Y.; Liu, X. Potential hormetic effects of cimetidine on aerobic composting of human feces from rural China. Sustainability 2022, 14, 14454. [Google Scholar] [CrossRef]
  22. Lin, L.; Yang, X.; Shen, Y.; Zhu, P.; Niu, S.; Alghashm, S.; Ding, G.; Wu, D.; Li, X. Inhibition of odor generation during the composting process of fecal sludge from rural toilets by decomposed compost backfilling. Bioresour. Technol. Rep. 2025, 29, 102065. [Google Scholar] [CrossRef]
  23. Miko, A.S.; Ibrahim, S. Assessment of heavy metal contamination in irrigated farmland and associated health risks in Kano State, Nigeria: A review. UMYU Sci. 2024, 3, 86–93. [Google Scholar] [CrossRef]
  24. Mian, H.R.; Hu, G.; Hewage, K.; Rodriguez, M.J.; Sadiq, R. Drinking water management strategies for distribution networks: An integrated performance assessment framework. J. Environ. Manag. 2023, 325, 116537. [Google Scholar] [CrossRef]
  25. Mishra, R.K.; Mentha, S.S.; Misra, Y.; Dwivedi, N. Emerging pollutants of severe environmental concern in water and wastewater: A comprehensive review on current developments and future research. Water Energy Nexus 2023, 6, 74–95. [Google Scholar] [CrossRef]
  26. Zhang, X.; Zhi, X.; Chen, L.; Shen, Z. Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed. Water Res. 2020, 178, 115835. [Google Scholar] [CrossRef]
  27. Zhai, Q.-Z. Determination of phosphorus by phosphorus molybdenum blue spectrophotometry by bismuth antimony sensitization. Bull Chem. Soc. Ethiopia 2023, 37, 1307–1313. [Google Scholar] [CrossRef]
  28. Method 3051A (SW-846); Microwave Assisted Acid Digestion of Sediments, Sludges, and Oils. Revision 1. U.S. Environmental Protection Agency: Washington, DC, USA, 2007.
  29. Liu, B.; Pop, M. ARDB—Antibiotic resistance genes database. Nucleic Acids Res. 2009, 37, D443–D447. [Google Scholar] [CrossRef] [PubMed]
  30. Zou, S.; Hu, R.; Liang, S.; Lu, T.; Kang, D.; Li, D. Assessment of health risk of antibiotics resistance genes from human disturbed habitat to wild animals: Metagenomic insights into availability and functional changes of gut microbiome. Ecotox Environ. Safe 2024, 285, 117117. [Google Scholar] [CrossRef] [PubMed]
  31. Lepane, V.; Depret, L.; Väli, A.-L.; Suursööt, K. Impact of seasonal climate change on optical and molecular properties of river water dissolved organic matter by HPLC-SEC and UV-vis spectroscopy. Chem. Biol. Technol. AG 2015, 2, 14. [Google Scholar] [CrossRef]
  32. Annadurai, P.; Kutralingam, K.; Thiyagarajan, C.; Priya, R.; Doraiswamy, U.; Lourdusamy, K. Agronomic biofortification of calcium in cabbage (Brassica Oleracea var capitata) applied with different sources of liming in Ca deficient acidic soil of Coonoor, The Nilgiris (Typic Dystropept). J. Appl. Nat. Sci. 2022, 14, 1286–1296. [Google Scholar] [CrossRef]
  33. Li, L.; Mao, K.; Ippolito, J.A.; Xing, W.; Chen, X.; Zhu, W.; Cheng, Y. Calcium amendments affect heavy metal bioavailability in acidic and calcareous soils. Inter. J. Environ. Sci. Technol. 2022, 19, 10067–10076. [Google Scholar] [CrossRef]
  34. Deng, Y.; Wang, M.; Tian, T.; Lin, S.; Xu, P.; Zhou, L.; Dai, C.; Hao, Q.; Wu, Y.; Zhai, Z.; et al. The Effect of Hexavalent Chromium on the Incidence and Mortality of Human Cancers: A Meta-Analysis Based on Published Epidemiological Cohort Studies. Front. Oncol. 2019, 9, 24. [Google Scholar] [CrossRef]
  35. Bakshi, A.; Panigrahi, A.K. Chromium Contamination in Soil and Its Bioremediation: An Overview. In Advances in Bioremediation and Phytoremediation for Sustainable Soil Management: Principles, Monitoring and Remediation; Malik, J.A., Ed.; Springer International Publishing: Cham, Switzerland, 2022; pp. 229–248. [Google Scholar]
  36. Wang, Y.; Su, H.; Gu, Y.; Song, X.; Zhao, J. Carcinogenicity of chromium and chemoprevention: A brief update. Onco Targets Ther. 2017, 10, 4065–4079. [Google Scholar] [CrossRef] [PubMed]
  37. Alam, S.; Velayudhan, S.M.; Bateki, C.A.; Malik, P.K.; Bhatta, R.; Buerkert, A.; König, S.; Schlecht, E. Seasonal variation in heavy metal intake and excretion by dairy cattle in an Indian megacity. Lives Sci. 2024, 286, 105520. [Google Scholar] [CrossRef]
  38. Mir, A.R.; Pichtel, J.; Hayat, S. Copper: Uptake, toxicity and tolerance in plants and management of Cu-contaminated soil. BioMetals 2021, 34, 737–759. [Google Scholar] [CrossRef] [PubMed]
  39. Sammons, S.; Brady, D.; Vahdat, L.; Salama, A. Copper suppression as cancer therapy: The rationale for copper chelating agents in BRAF mutated melanoma. Melanoma Manag. 2016, 3, 207–216. [Google Scholar] [CrossRef]
  40. Wenting, E.; Siepel, H.; Jansen, P.A. Variability of the ionome of wild boar (Sus scrofa) and red deer (Cervus elaphus) in a Dutch national park, with implications for biomonitoring. Biol. Trace Elem. Res. 2024, 202, 2518–2546. [Google Scholar] [CrossRef]
  41. Cai, L.-M.; Wang, Q.-S.; Luo, J.; Chen, L.-G.; Zhu, R.-L.; Wang, S.; Tang, C.-H. Heavy metal contamination and health risk assessment for children near a large Cu-smelter in central China. Sci. Total Environ. 2019, 650, 725–733. [Google Scholar] [CrossRef]
  42. Pan, J.; Zheng, N.; An, Q.; Li, Y.; Sun, S.; Wang, S.; Ji, Y.; Li, N. The effects of cadmium-copper stress on the accumulation of antibiotic-resistance genes in soil and pakchoi leaves. Soil. Biol. Biochem. 2024, 191, 109362. [Google Scholar] [CrossRef]
  43. Liu, H.; Yu, Z.; Wu, Z.; Xu, X. Characterization of red mud-based curing agent for curing high concentration copper contaminated soil. Int. J. Energy 2024, 4, 22–26. [Google Scholar] [CrossRef]
  44. Huang, Y.; Chen, Q.; Deng, M.; Japenga, J.; Li, T.; Yang, X.; He, Z. Heavy metal pollution and health risk assessment of agricultural soils in a typical peri-urban area in southeast China. J. Environ. Manag. 2018, 207, 159–168. [Google Scholar] [CrossRef]
  45. Schoofs, H.; Schmit, J.; Rink, L. Zinc Toxicity: Understanding the Limits. Molecules 2024, 29, 3130. [Google Scholar] [CrossRef]
  46. Hacisalihoglu, G. Zinc (Zn): The last nutrient in the alphabet and shedding light on Zn efficiency for the future of crop production under suboptimal Zn. Plants 2020, 9, 1471. [Google Scholar] [CrossRef] [PubMed]
  47. Sun, T.; Sun, J.; Liu, Y.; Ren, Y.; Li, Y.; Shi, C.; Nasr, A.; Tang, Z.; Abozeid, A. Metabolome and transcriptome analyses provide new insights into the mechanisms underlying the enhancement of medicinal component content in the roots of Acanthopanax senticosus (Rupr. et Maxim.) Harms through foliar application of zinc fertilizer. Front. Genet. 2023, 14, 1259674. [Google Scholar] [CrossRef] [PubMed]
  48. Shinde, D.; Mahajan, D.; Pawar, A.; Kale, M.; Chakane, S. Trace Metal Accumulation in Water, Soil and Crop Plants along the Basin of Ujjani Reservoir, India. Adv. Zool. Bot. 2020, 8, 453–460. [Google Scholar] [CrossRef]
  49. Li, X.; Zhou, Y.; Zhang, J. Status and associated human health risk of zinc accumulation in agricultural soils across China. Process Saf. Environ. 2021, 146, 867–876. [Google Scholar] [CrossRef]
  50. Reimann, C.; Fabian, K.; Flem, B.; Englmaier, P. The large-scale distribution of Cu and Zn in sub- and topsoil: Separating topsoil bioaccumulation and natural matrix effects from diffuse and regional contamination. Sci. Total Environ. 2019, 655, 730–740. [Google Scholar] [CrossRef]
  51. Kaur, H.; Garg, N. Zinc toxicity in plants: A review. Planta 2021, 253, 129. [Google Scholar] [CrossRef]
  52. Mai, X.; Tang, J.; Tang, J.; Zhu, X.; Yang, Z.; Liu, X.; Zhuang, X.; Feng, G.; Tang, L. Research progress on the environmental risk assessment and remediation technologies of heavy metal pollution in agricultural soil. J. Environ. Sci. 2025, 149, 1–20. [Google Scholar] [CrossRef]
  53. Azhar, U.; Ahmad, H.; Shafqat, H.; Babar, M.; Shahzad Munir, H.M.; Sagir, M.; Arif, M.; Hassan, A.; Rachmadona, N.; Rajendran, S.; et al. Remediation techniques for elimination of heavy metal pollutants from soil: A review. Environ. Res. 2022, 214, 113918. [Google Scholar] [CrossRef]
  54. Odirile, P.T.; Obuseng, V.C.; Moshoeshoe, M.; Tshenyego, L.; Mbongwe, B. Assessment of faecal sludge quality, heavy metal contamination, and ecological risk: Implications for sustainable agriculture. Environ. Monit. Assess. 2024, 196, 1270. [Google Scholar] [CrossRef]
  55. Peng, S.; Zhang, H.; Song, D.; Chen, H.; Lin, X.; Wang, Y.; Ji, L. Distribution of antibiotic, heavy metals and antibiotic resistance genes in livestock and poultry feces from different scale of farms in Ningxia, China. J. Hazard Mater. 2022, 440, 129719. [Google Scholar] [CrossRef]
  56. Huang, J.; Wang, Z.; Chen, Z.; Liang, H.; Li, X.; Li, B. Occurrence and removal of antibiotic resistance in nationwide hospital wastewater deciphered by metagenomics approach—China, 2018-2022. China CDC Wkly. 2023, 5, 1023–1028. [Google Scholar] [CrossRef]
  57. Wang, F.Q. Quantitative Methods and Applications in GIS, 1st ed.; CRC Press: Boca Raton, FL, USA, 2006. [Google Scholar] [CrossRef]
  58. Pei, R.; Kim, S.C.; Carlson, K.H.; Pruden, A. Effect of river landscape on the sediment concentrations of antibiotics and corresponding antibiotic resistance genes (ARG). Water Res. 2006, 40, 2427–2435. [Google Scholar] [CrossRef]
  59. Zhao, W.; Wang, B.; Yu, G. Antibiotic resistance genes in China: Occurrence, risk, and correlation among different parameters. Environ. Sci. Pollut. Res. 2018, 25, 21467–21482. [Google Scholar] [CrossRef] [PubMed]
  60. Cedeño-Muñoz, J.S.; Aransiola, S.A.; Reddy, K.V.; Ranjit, P.; Victor-Ekwebelem, M.O.; Oyedele, O.J.; Pérez-Almeida, I.B.; Maddela, N.R.; Rodríguez-Díaz, J.M. Antibiotic resistant bacteria and antibiotic resistance genes as contaminants of emerging concern: Occurrences, impacts, mitigations and future guidelines. Sci. Total Environ. 2024, 952, 175906. [Google Scholar] [CrossRef] [PubMed]
  61. An, X.-L.; Su, J.-Q.; Li, B.; Ouyang, W.-Y.; Zhao, Y.; Chen, Q.-L.; Cui, L.; Chen, H.; Gillings, M.R.; Zhang, T.; et al. Tracking antibiotic resistome during wastewater treatment using high throughput quantitative PCR. Environ. Int. 2018, 117, 146–153. [Google Scholar] [CrossRef] [PubMed]
  62. Hubeny, J.; Harnisz, M.; Korzeniewska, E.; Buta, M.; Zieliński, W.; Rolbiecki, D.; Giebułtowicz, J.; Nałęcz-Jawecki, G.; Płaza, G. Industrialization as a source of heavy metals and antibiotics which can enhance the antibiotic resistance in wastewater, sewage sludge and river water. PLoS ONE 2021, 16, e0252691. [Google Scholar] [CrossRef]
  63. Li, H.; Tan, L.; Zhang, C.; Wei, X.; Wang, Q.; Li, Q.; Zheng, X.; Xu, Y. Spatial distribution of bacterial resistance towards antibiotics of rural sanitation system in China and its potential link with diseases incidence. J. Environ. Sci. 2023, 127, 361–374. [Google Scholar] [CrossRef]
Sustainability 17 07088 g001
Figure 1. Locations of the study area and sample collecting region.
Figure 1. Locations of the study area and sample collecting region.
Sustainability 17 07088 g001
Sustainability 17 07088 g002
Figure 2. Physiochemical characteristics of feces in different regions and seasons: (a) moisture content (MC), (b) pH, and (c) electrical conductivity (EC).
Figure 2. Physiochemical characteristics of feces in different regions and seasons: (a) moisture content (MC), (b) pH, and (c) electrical conductivity (EC).
Sustainability 17 07088 g002
Sustainability 17 07088 g003
Figure 3. Spatial and temporal distribution of nutrient elements in fecal matter of rural toilets: (a) total nitrogen (TN), (b) total phosphorous (TP), (c) total potassium (TK), and (d) organic matter (OM).
Figure 3. Spatial and temporal distribution of nutrient elements in fecal matter of rural toilets: (a) total nitrogen (TN), (b) total phosphorous (TP), (c) total potassium (TK), and (d) organic matter (OM).
Sustainability 17 07088 g003
Sustainability 17 07088 g004
Figure 4. Spatial and temporal distribution of calcium (Ca) content in fecal matter of rural toilets.
Figure 4. Spatial and temporal distribution of calcium (Ca) content in fecal matter of rural toilets.
Sustainability 17 07088 g004
Sustainability 17 07088 g005
Figure 5. Spatial and temporal distribution of chromium (Cr) content in fecal matter of rural toilets.
Figure 5. Spatial and temporal distribution of chromium (Cr) content in fecal matter of rural toilets.
Sustainability 17 07088 g005
Sustainability 17 07088 g006
Figure 6. Temporal and spatial distribution of copper (Cu) content in fecal matter of rural toilets.
Figure 6. Temporal and spatial distribution of copper (Cu) content in fecal matter of rural toilets.
Sustainability 17 07088 g006
Sustainability 17 07088 g007
Figure 7. Temporal and spatial distribution of zinc (Zn) content in fecal matter of rural toilets.
Figure 7. Temporal and spatial distribution of zinc (Zn) content in fecal matter of rural toilets.
Sustainability 17 07088 g007
Sustainability 17 07088 g008
Figure 8. Heat map of top 50 pathogenic microorganisms (PMs) at the genus level. AHfuyangdong, winter samples from Funan, Anhui Province; AHwuhuchun, spring samples from Wuhu, Anhui Province; GXnanningxia, summer samples from Nanning, Guangxi Province; JSnanjingqiu, autumn samples from Nanjing, Jiangsu Province.
Figure 8. Heat map of top 50 pathogenic microorganisms (PMs) at the genus level. AHfuyangdong, winter samples from Funan, Anhui Province; AHwuhuchun, spring samples from Wuhu, Anhui Province; GXnanningxia, summer samples from Nanning, Guangxi Province; JSnanjingqiu, autumn samples from Nanjing, Jiangsu Province.
Sustainability 17 07088 g008
Sustainability 17 07088 g009
Figure 9. Venn diagram of pathogenic microorganisms (PMs) at the genus level. AHwuhuchun, spring samples from Wuhu, Anhui Province; GXnanningxia, summer samples from Nanning, Guangxi Province; JSnanjingqiu, autumn samples from Nanjing, Jiangsu Province; AHfuyangdong, winter samples from Funan, Anhui Province.
Figure 9. Venn diagram of pathogenic microorganisms (PMs) at the genus level. AHwuhuchun, spring samples from Wuhu, Anhui Province; GXnanningxia, summer samples from Nanning, Guangxi Province; JSnanjingqiu, autumn samples from Nanjing, Jiangsu Province; AHfuyangdong, winter samples from Funan, Anhui Province.
Sustainability 17 07088 g009
Sustainability 17 07088 g010
Figure 10. Venn diagram of antibiotic resistance gene (ARGs) composition. AHwuhuchun, spring samples from Wuhu, Anhui; GXnanningxia, summer samples from Nanning, Guangxi; JSnanjingqiu, autumn samples from Nanjing, Jiangsu; AHfuyangdong, winter samples from Funan, Anhui.
Figure 10. Venn diagram of antibiotic resistance gene (ARGs) composition. AHwuhuchun, spring samples from Wuhu, Anhui; GXnanningxia, summer samples from Nanning, Guangxi; JSnanjingqiu, autumn samples from Nanjing, Jiangsu; AHfuyangdong, winter samples from Funan, Anhui.
Sustainability 17 07088 g010
Table 1. Sample collection and regional characteristics.
Table 1. Sample collection and regional characteristics.
PlaceSpring
March		Summer
August		Autumn
October		Winter
January		Economic
Activity		Mean Summer
Temp. (°C)		Mean Winter
Temp. (°C)
Wuhu,
Anhui Province		①
(2019)		②
(2019)		③
(2019)		-Manufacturing 322
Fuyang,
Anhui Province		---④
(2020)		Agriculture 331
Nanning,
Guangxi Province		-⑤
(2020)		-⑥
(2019)		Trading3410
Nanjing,
Jiangsu Province		-⑦
(2020)		⑧
(2020)		⑨
(2020)		Technology320
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lin, L.; Shen, Y.; Ding, G.; Alghashm, S.; Aye, S.L.; Li, X. Spatial and Temporal Distribution of Conversational and Emerging Pollutants in Fecal Sludge from Rural Toilets, China. Sustainability 2025, 17, 7088. https://doi.org/10.3390/su17157088

AMA Style

Lin L, Shen Y, Ding G, Alghashm S, Aye SL, Li X. Spatial and Temporal Distribution of Conversational and Emerging Pollutants in Fecal Sludge from Rural Toilets, China. Sustainability. 2025; 17(15):7088. https://doi.org/10.3390/su17157088

Chicago/Turabian Style

Lin, Lin, Yilin Shen, Guoji Ding, Shakib Alghashm, Seinn Lei Aye, and Xiaowei Li. 2025. "Spatial and Temporal Distribution of Conversational and Emerging Pollutants in Fecal Sludge from Rural Toilets, China" Sustainability 17, no. 15: 7088. https://doi.org/10.3390/su17157088

APA Style

Lin, L., Shen, Y., Ding, G., Alghashm, S., Aye, S. L., & Li, X. (2025). Spatial and Temporal Distribution of Conversational and Emerging Pollutants in Fecal Sludge from Rural Toilets, China. Sustainability, 17(15), 7088. https://doi.org/10.3390/su17157088

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop