Monitoring-Based Comprehensive Environmental Risk Assessment of Multi-Medium Pollutants and Spatiotemporal Differences in Three Typical Cement Plants

Monitoring-Based Comprehensive Environmental Risk Assessment of Multi-Medium Pollutants and Spatiotemporal Differences in Three Typical Cement Plants | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Monitoring-Based Comprehensive Environmental Risk Assessment of Multi-Medium Pollutants and Spatiotemporal Differences in Three Typical Cement Plants shuai li, jie jiang, xin li, guanhou chen, bin li, rong wang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8838504/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract To support precise environmental management of cement plants, this study conducted a systematic monitoring and comprehensive risk assessment of multi-medium pollutants (noise, atmospheric pollutants, wastewater pollutants) from three typical cement plants (BC, NC, ZL) in the first and second quarters of 2024. Field monitoring data were used to evaluate single-factor risks: noise risk via national standard compliance evaluation, atmospheric non-carcinogenic risk via hazard index (HI), and wastewater ecological risk via risk quotient (RQ). Comprehensive risk integration was further performed to clarify spatiotemporal differences and identify key risk sources. Results showed that all cement plants met noise emission standards (normalized risk value = 1.000), with no excessive nuisance risk. All plants exhibited potential atmospheric non-carcinogenic risks (HI > 1), with BC cement plant having the highest air pollution risk (HI: 2.730–3.043) dominated by NOₓ and particulate matter. ZL cement plant presented high wastewater ecological risk due to excessive total phosphorus (TP, RQ = 1.310–1.500). Comprehensive risk ranked as ZL2 > BC1 > ZL1 > BC2 > NC2 > NC1, showing obvious seasonal variations driven by production load adjustment and pollution treatment efficiency. This study provides a standardized monitoring-assessment framework for multi-medium pollutants in cement plants, and the findings offer targeted technical support for regional industrial pollution management. Cement plant Multi-medium pollutants Environmental risk assessment Spatiotemporal difference Risk quotient Hazard index Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction The cement industry serves as a vital pillar of the global construction sector, playing an irreplaceable role in urbanization and infrastructure development (Jena et al., 2025 ). However, cement production involves complex processes such as raw material calcination, clinker grinding, and fuel combustion, inevitably generating multiple types of pollutants. These include noise, air pollutants (such as nitrogen oxides, particulate matter, and total suspended solids), and wastewater contaminants (such as heavy metals, total phosphorus, and chemical oxygen demand). These pollutants trigger a series of environmental impacts: air pollutants pose non-carcinogenic health risks to surrounding populations, wastewater pollutants create ecological risks to receiving water bodies, and persistent noise emissions may cause disturbance to residents (Salazar-Rojas et al., 2025 ). As global environmental regulations become increasingly stringent, the comprehensive environmental risk assessment of multi-media pollutants from cement plants has emerged as a key research focus in industrial environmental management (Bărbulescu and Hosen, 2025 ). Research on pollution from cement plants has achieved certain progress. Regarding air pollution, most studies have focused on the concentration characteristics of particulate matter or nitrogen oxides and their potential health risks, confirming their adverse effects on the respiratory system (Kane et al., 2024 ). Concerning wastewater pollution, relevant research has primarily concentrated on removal technologies for heavy metals or nutrients, with less attention paid to ecological risk characterization based on the risk quotient (RQ). Regarding noise pollution, research has largely been confined to monitoring emission levels, lacking integrated consideration of noise risks within the comprehensive environmental risk framework for cement plants (Rawat et al., 2025). It is worth noting that current research exhibits significant shortcomings: (1) Most studies focus solely on pollution assessments for single media, neglecting the synergistic effects of combined risks from multiple pollutants (noise-air-water). This approach fails to comprehensively reflect the overall environmental impact of cement plants; (2) Few studies address temporal variations in pollution risks (e.g., seasonal changes), making it difficult to clarify the dynamic patterns of risk driven by production adjustments and meteorological factors; (3) Targeted research on integrated risk ranking and key risk source identification for multiple cement plants within the same region is insufficient, limiting the formulation of precise regional pollution control strategies (Nwogu et al., 2025). To address these gaps, this study selected three representative cement plants (BC, NC, ZL) as research subjects and systematically assessed the environmental risks of multi-media pollutants during the first and second quarters of 2024. The specific research objectives are: (1) to clarify the emission levels of noise, air pollutants, and wastewater pollutants from these three cement plants and their single-factor risk characteristics; (2) to analyze the spatiotemporal differences in comprehensive environmental risks among different cement plants and across different quarters; (3) to identify key risk sources and propose targeted pollution control strategies. This study aims to establish a multidimensional environmental risk assessment framework for cement plants, provide scientific basis for integrated regional industrial pollution management, and offer reference for optimizing pollution control measures in the cement industry. 2. Materials and methods 2.1 Overview of study area and target cement plant The study area encompasses Mianyang City and Nanchong City, located in the northwest and northeast of the Sichuan Basin in southwest China, respectively. Mianyang City (30°42′–31°29′ N, 103°45′–105°43′ E) has an annual average temperature of 16.3–17.7°C and annual average precipitation of 825–1417 mm, primarily concentrated during the summer months (June to August)(Liu et al., 2024a). Nanchong City (30°35′ N − 31°51′ N, 105°27′ E − 106°58′ E) has an annual average temperature of 17.4°C and annual precipitation ranging from 980 to 1150 mm. Both cities are major industrial hubs in Sichuan Province, with cement production serving as a vital pillar industry supporting local infrastructure development (Zhang et al., 2023). However, the intensive discharge of multiple pollutants (exhaust gases, wastewater, and noise) from cement plants in these regions poses potential threats to the local ecological environment and human health. 2.2 Data source and monitoring methods All environmental monitoring data in this study were obtained from supervisory monitoring conducted by Xipu Technology Co., Ltd. during the first and second quarters of 2024. This monitoring complied with the technical requirements of national environmental monitoring standards. Monitoring indicators covered three environmental media: exhaust gases, wastewater, and noise. Monitoring frequency, monitoring point layout, and technical specifications were strictly implemented in accordance with relevant national and industry standards. Waste gas monitoring: Key pollutants monitored include total suspended particulates, ammonia, hydrogen sulfide, odor concentration, particulate matter, sulfur dioxide, nitrogen oxides, fluorides, and dioxins. Monitoring employs a continuous automatic monitoring system (Model: TH-2000B) with detection limits as follows: total suspended particulates (TSP): 0.007 mg/m³, ammonia (NH 3 ): 0.01 mg/m³, hydrogen sulfide (H 2 S): 0.001 mg/m³, particulate matter (PM): 1.0 mg/m³, SO 2 : 3 mg/m³, NO X : 3 mg/m³. This monitoring complies with the Technical Specification for Monitoring of Waste Gas from Fixed Pollution Sources (HJ/T 75-2017). For each cement plant, four monitoring points will be established at the plant boundary, including one upwind point and three downwind points (downwind points arranged along the prevailing wind direction of the study area). Monitoring will be conducted continuously for 24 hours daily, with data recorded at one-hour intervals. Fifteen days of valid monitoring data will be collected each quarter (excluding days with extreme weather conditions such as heavy rain and strong winds). Wastewater: The monitored parameters include pH, chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD 5 ), suspended solids (SS), ammonia nitrogen (NH 3 -N), total phosphorus (TP), and specific heavy metals (hexavalent chromium (Cr), lead (Pb), cadmium (Cd), mercury (Hg), arsenic (As)). pH was measured using a pH meter (PHBJ-260); COD was determined via the potassium dichromate digestion method (detection limit: 4 mg/L); SS was measured by gravimetric analysis (detection limit: 4 mg/L); heavy metals were analyzed using atomic fluorescence spectrophotometry/ atomic absorption spectrophotometer (AFS-8500/TAS-990AFG), with detection limits of 0.004 mg/L for chromium, 0.3 µg/L for arsenic, 0.001 mg/L for cadmium, and 0.004 µg/L for mercury. Monitoring procedures followed the guidelines outlined in “Water Quality - Sampling and Sample Preparation for Physical and Chemical Analysis” (GB/T 12998 − 2008). A monitoring point is established at the final discharge outlet of each factory's wastewater treatment system. Samples are collected every 3 days, with 3 parallel samples taken each time. A total of 15 valid sample sets is obtained each quarter. Noise: During daytime (06:00–22:00) and nighttime (22:00–06:00), the equivalent continuous A-weighted sound level (Leq) at the factory boundary was monitored using a sound level meter (Model: AWA5688). The meter has a measurement range of 30–130 dB(A) and an accuracy of ± 1 dB(A). Monitoring activities were conducted in accordance with the “Specification for Noise Measurement at Boundaries of Industrial Enterprises” (GB/T 12348 − 2008). Six monitoring points were evenly distributed along the perimeter of each factory. Each point was monitored for 10 minutes, with the average value serving as the Leq value for that point. Monitoring was conducted every 7 days, yielding 5 valid monitoring periods per quarter. All monitoring data have been aggregated and verified to exclude invalid data (e.g., data with obvious measurement errors or affected by extreme weather conditions). Aggregated statistical information for noise, exhaust emissions, and wastewater pollutant monitoring data is presented in Tables 1 – 3 . 2.3 Risk Assessment Framework and Methodology This study employs a screening-level risk assessment framework characterized by conservative assumptions and simplified calculation methods, suitable for identifying potential high-risk pollutants and sources under conditions of limited data. The framework comprises four core steps: hazard identification, exposure assessment, toxicity assessment, and risk characterization. 2.3.1 Noise pollution risk assessment Noise Disturbance Risk Assessment The risk of noise disturbance is assessed using the threshold comparison method, referencing the Environmental Noise Quality Standard (GB 3096 − 2008). The boundaries of the three cement plants are located within Category 2 zones (mixed residential, commercial, and industrial areas), where the daytime standard limit is Leq 60 dB(A) and the nighttime limit is 50 dB(A). The calculation method for the degree of noise exceedance is as follows: Degree of Exceedance (dB(A)) = Measured Leq - Standard Limit (Easton et al., 2024 ). 2.3.2 Waste gas risk assessment Reference concentration (RfC, milligrams per cubic meter) represents the pollutant concentration that poses no adverse health effects even with long-term exposure, serving as a toxicity indicator. Reference concentration values for PM₁₀ and NO₂ were obtained from China's Technical Guidelines for Environmental Health Risk Assessment of Pollutants. For instance, the reference concentration for TSP and NH₃ is 0.002 mg/m³, for H₂S it is 0.06 mg/m³, and for malodorous gases it is 20 mg/m³. The Hazard Quotient (HQ) is used to describe the non-carcinogenic risk of a single pollutant, while the Hazard Index (HI) is used to describe the combined non-carcinogenic risk of multiple pollutants. Their calculation formulas are as follows: HQ = C / RfC HI = ΣHQ According to the U.S. Environmental Protection Agency's guidance principles, if the HI is less than 1, it indicates that the non-carcinogenic risk is acceptable; whereas if the HI is greater than or equal to 1, it indicates that the risk warrants attention and requires a more detailed assessment (Qin et al., 2026 ). 2.3.3 Wastewater risk assessment The ecological risk of wastewater pollutants was assessed using the risk quotient (RQ) method, which is widely applied in screening-level ecological risk assessments. The risk quotient is calculated as the ratio of the measured environmental concentration (MEC) to the predicted no-effect concentration (PNEC): RQ = MEC / PNEC MEC (mg/L) refers to the maximum detected concentration of pollutants in wastewater from each facility during the corresponding quarter; PNEC (milligrams per liter) denotes the concentration at which no adverse ecological effects are predicted to occur. PNEC values for different pollutants were obtained from the European Chemicals Agency (ECHA) risk assessment reports and China's Surface Water Quality Standards.Based on the RQ value, ecological risks are categorized into three levels: low risk (RQ < 0.1), moderate risk (0.1 ≤ RQ < 1), and high risk (RQ ≥ 1) (Sim et al., 2024). 3. Results and discussion 3.1 Noise pollution risk assessment Noise pollution generated by cement plants directly impacts the living environment and physical and mental health of residents surrounding the facilities (Razai et al., 2025). This section employs a threshold comparison method based on national environmental quality standards to assess the noise disturbance risk for three target cement plants (BC, NC, ZL) during the first and second quarters of 2024 (referred to as BC1, BC2, NC1, NC2, ZL1, and ZL2, respectively). The specific results of daytime and nighttime noise monitoring at each factory boundary are shown in Table 1 and Fig. 1 a. As indicated in the table, all measured Leq values for the three factories during both quarters remained below the corresponding standard limits, with no instances of noise pollution exceeding the threshold detected (Pradeep and Nagendra, 2024 ). Specifically, for daytime noise: Measurements ranged from 47.367 dB(A) (NC2) to 56.733 dB(A) (NC1), all below the 60 dB(A) standard limit. The maximum deviation from the standard limit was 12.633 dB(A) (NC2), and the minimum deviation was 3.267 dB(A) (NC1). For nighttime noise: measured values ranged from 41.467 dB(A) (ZL2) to 49.800 dB(A) (NC1), all below the 50 dB(A) standard limit. Among these, NC1's nighttime noise was closest to the standard limit, with a difference of only 0.200 dB(A), while ZL2 showed the largest deviation, with a gap of 8.533 dB(A) from the standard limit. All noise risks in the monitored groups of this study were classified as “no risk.” Among them, although the NC1 group's nighttime noise levels came closest to the standard limit, the measured values remained below the standard threshold, thus posing no disturbance risk to residents. The ZL2 group exhibited the lowest daytime and nighttime noise levels across all groups, indicating that ZL Cement Plant achieved relatively optimal noise control performance during the second quarter (Quader et al., 2024 ). In summary, noise emissions from these three cement plants during the first and second quarters of 2024 complied with national environmental quality standards, posing no risk of noise disturbance to residents. From the perspective of temporal and spatial variation, NC Plant exhibited the highest daytime noise levels across all categories during the first quarter, while nighttime noise levels remained generally low at all plants. Noise levels at each plant showed a downward trend in the second quarter compared to the first quarter, potentially attributable to production process optimization and enhanced noise control measures implemented by the plants.(Gao and Ye, 2025 ) Table 1 Summary of Noise Pollution Group Daytime noise (dB) Standard value (dB) Night noise (dB) Standard value (dB) BC1 53.167 60.000 48.667 50.000 BC2 53.500 60.000 48.067 50.000 NC1 56.733 60.000 49.800 50.000 NC2 47.367 60.000 48.550 50.000 ZL1 52.900 60.000 49.100 50.000 ZL2 49.367 60.000 41.467 50.000 3.2 Atmospheric pollution risk assessment 3.2.1 Atmospheric Pollutant Monitoring Level Overview Air pollutants emitted during cement production—such as particulate matter, sulfur oxides, and nitrogen oxides—are significant factors affecting regional air quality and human health (Yan et al., 2025).Detailed monitoring results for each group of air pollutants are shown in Table 2 and Fig. 1 b. As evident from this table, concentration levels of various pollutants exhibit significant differences between different cement plants and regions, with characteristic pollutants displaying distinct concentration patterns: Particulate Matter Pollutants (TSP and PM): TSP concentrations varied significantly across cement plants, with the highest levels observed at BC Plant (0.494–0.557 mg/m³), which was 1.86 times higher than NC Plant (0.238–0.262 mg/m³) and 1.87 times higher than ZL Plant (0.263–0.269 mg/m³). − 0.262 mg/m³) and ZL Plant (0.263–0.269 mg/m³). For PM, ZL1 exhibited the highest concentration (6.800 mg/m³), followed by BC1 (5.600 mg/m³), while NC2 recorded the lowest concentration (3.867 mg/m³). From a seasonal variation perspective, TSP concentrations at BC plant decreased by 11.31% from Q1 to Q2, while PM concentrations decreased by 11.30%. At ZL plant, PM concentrations dropped by 29.41% from Q1 to Q2, showing a significant downward trend. Gaseous pollutants (NH 3 , H 2 S, SO 2 , NO X , fluorides): H 2 S concentrations were relatively low across all groups, ranging from 0.002 to 0.004 mg/m³, with no significant differences observed between plantations or seasons. NH 3 concentrations peaked in BC1 (0.490 mg/m³) and were lowest in ZL1 (0.060 mg/m³). SO 2 exhibited the most pronounced plantation variation, with ZL Plant concentrations (4.667–7.667 mg/m³) being 3.34–5.61 times higher than those at BC Plant (1.367–1.400 mg/m³) and NC Plant (1.333–1.433 mg/m³). while ZL1's SO 2 concentration was 64.30% higher than ZL2's. NO X concentrations peaked at BC Plant (69.667–82.667 mg/m³), followed by NC Plant (44.667–56.667 mg/m³), with ZL Plant recording the lowest levels in Q1 (22.333 mg/m³); NOx concentrations at the BC plant decreased by 15.73% from Q1 to Q2, showing a downward trend. Fluoride concentrations were extremely high in ZL2 (0.822 mg/m³), 2.97 to 27.40 times higher than in other groups. Odor and polychlorodibenzo-p-dioxins (PCDDs): Odor concentrations were highest in the BC2 and ZL2 groups (both at 13 mg/m³) and lowest in the NC1 group (7.067 mg/m³). PCDD concentrations were relatively low across all groups, ranging from 0.003 to 0.013 TEQ/m 3 , with the highest concentration observed in the BC2 group (0.013 TEQ/m 3 ). Overall, the concentrations of air pollutants at these three cement plants exhibit distinct site-specific and seasonal characteristics: BC Plant primarily features high concentrations of TSP and NOX, ZL Plant predominantly shows elevated levels of SO2 and fluorides (especially at ZL2), while NC Plant generally has relatively lower concentrations for most pollutants. From a seasonal perspective, most pollutants at BC and ZL plants showed a decreasing trend from the first to the second quarter. This may be attributed to production process optimization, enhanced end-of-pipe treatment facilities, and changes in meteorological conditions (for instance, increased precipitation and improved dispersion conditions in the second quarter)(Feng et al., 2025 ). The monitoring levels of the aforementioned air pollutants provide foundational data support for subsequent health risk assessments of key pollutants(Moffa et al., 2025). 3.2.2 Atmospheric Pollutant Health Risk Assessment Based on air pollutant monitoring data (Table 2 ) and Fig. 2 , we assessed the non-carcinogenic health risks for the first and second quarters of 2024 at three cement plants (BC, NC, ZL) using the Hazard Quotient (HQ) and Hazard Index (HI) models recommended by the U.S. Environmental Protection Agency (EPA). HQ describes the non-carcinogenic risk for a single pollutant, while HI (the sum of the hazard quotients for all pollutants) reflects the combined non-carcinogenic risk from mixed pollutants (He et al., 2025 ). Concentration values of major air pollutants and the comprehensive health index values for each monitoring group (BC1, BC2, NC1, NC2, ZL1, ZL2) are shown in Fig. 2 . As shown in Table S1 , the health risk values for different air pollutants vary significantly among these three cement plants, and each pollutant contributes differently to the overall health risk. NO X : As the primary risk factor at the BC factory, its concentration ratios in BC1 and BC2 were 0.827 and 0.697 respectively, both ranking highest within their respective groups. Although the concentration ratios of NO X at NC and ZL plants (0.447–0.567 and 0.223–0.517) were lower than those at BC plant, they still ranked among the top three pollutants by concentration ratio within each group. This is because NOX from cement production processes (such as calcination) exhibits strong respiratory toxicity, with long-term exposure causing damage to the respiratory and cardiovascular systems (Nomura et al., 2025 ). PM and TSP: These two particulate pollutants represent significant risk factors across all three factories. At the ZL1 factory, PM exhibited the highest HQ value (0.680), followed by BC1 (0.560); At the BC plant, the HQ values for TSP (0.494–0.557) were significantly higher than those at the NC plant (0.238–0.262) and the ZL plant (0.263–0.269), consistent with the particulate matter monitoring concentration characteristics described in Section 3.2.1 . Particulate matter can penetrate deep into the respiratory tract and even enter the bloodstream, triggering chronic diseases such as asthma and pulmonary fibrosis (Wang et al., 2024 ). Odor: In BC2 and ZL2, the HQ values for odor are relatively high (both 0.650), 1.84 times higher than the value in NC1 (0.353, the lowest value). These odor pollutants (primarily volatile organic compounds and ammonia) cause sensory discomfort and psychological stress, and certain components possess potential toxic effects (Wu et al., 2024 ).Other Pollutants: The hazard index values for H₂S, SO₂, fluorides, and PCDDs were relatively low across all groups, with most values below 0.3. This indicates their respective non-carcinogenic risks are negligible. However, it should be noted that the hazard index value for fluoride in the ZL2 group was 0.274, which was 2.49 to 27.40 times higher than in other groups. This indicates that the ZL plant should focus on controlling fluoride emissions during the second quarter. The overall non-carcinogenic risk level (denoted as HI) for each group exhibits significant spatial and temporal variations. Spatial differences (Comparisons Among Cement Plants): The BC plant exhibits the highest overall health risk, with HI values of 3.063 (BC1) and 2.804 (BC2), representing 1.49 to 1.76 times higher than the NC plant (1.738–2.049), which has the lowest risk among the three cement plants. ZL Plant's HI values of 1.940 (ZL1) and 2.689 (ZL2) fall between those of BC and NC plants. This spatial variation primarily stems from the combined effects of high NOx, TSP, and PM concentrations at BC Plant, collectively contributing to its highest overall risk (Wang et al., 2025). Time difference (Seasonal comparison with cement plant): (1) BC Plant: From Q1 to Q2, HI decreased by 8.46%, associated with declines in HQ values for TSP, NOX, and PM (consistent with the decreasing trend in their monitored concentrations in Section 3.2.1 ); (2) NC Plant: From Q1 to Q2, HI increased by 17.90%, primarily due to higher HQ values for NH₃, H₂S, odor, and NOₓ; (3) ZL Plant: From Q1 to Q2, HI increased by 38.61%, primarily due to significant increases in fluoride HQ values (from 0.011 to 0.274) and odor HQ values (from 0.400 to 0.650), along with an increase in NO X HQ values. Seasonal variations in HI may result from the combined effects of production load adjustments, operational efficiency of end-of-pipe treatment facilities, and meteorological conditions (such as higher temperatures in the second quarter intensifying photochemical reactions, which may enhance the toxicity of certain pollutants) (Taha et al., 2025 ). Risk Level Assessment: During Q1 and Q2, all HI values for these three plants exceeded 1 (ranging from 1.738 to 3.063). This indicates that the combined air pollutants emitted by these cement plants pose potential non-carcinogenic health risks to exposed populations in the surrounding areas. Among them, BC1 presents the highest risk (HI = 3.063) and requires priority attention and implementation of risk mitigation measures(Ciarlantini et al., 2025). In summary, the air pollutants emitted by these three cement plants pose significant non-carcinogenic health risks, with Plant BC being the primary risk source and NO X , PM, and TSP being the main risk factors. The seasonal variations in health risks differ among the plants, influenced by multiple factors including production patterns and meteorological conditions. These findings provide targeted evidence for developing subsequent air pollution control and health risk management strategies for these three cement plants. Table 2 Summary Table of Atmospheric Pollutant Concentrations Group TSP (mg/m 3 ) NH 3 (mg/m 3 ) H 2 S (mg/m 3 ) Odor concentration (mg/m 3 ) PM (mg/m 3 ) SO 2 (mg/m 3 ) NO X (mg/m 3 ) Fluoride (mg/m 3 ) PCDDs (TEQ/m3) HI BC1 0.557 0.490 0.003 8.000 5.600 1.367 82.667 0.277 0.005 3.063 BC2 0.494 0.223 0.004 13.000 4.967 1.400 69.667 0.033 0.013 2.804 NC1 0.238 0.140 0.002 7.067 4.500 1.333 44.667 0.030 0.003 1.738 NC2 0.262 0.197 0.003 9.167 3.867 1.433 56.667 0.106 0.005 2.049 ZL1 0.263 0.060 0.003 8.000 6.800 7.667 22.333 0.033 0.004 1.940 ZL2 0.269 0.260 0.004 13.000 4.800 4.667 51.667 0.822 0.005 2.689 3.3 Wastewater pollution risk assessment 3.2.1 Wastewater pollutant monitoring level overview Wastewater discharged from cement production processes contains various pollutants (such as organic matter, nutrients, and heavy metals). If not properly treated, it may pose a potential threat to the water quality and aquatic ecosystems of receiving water bodies (Bi et al., 2024 ).Detailed monitoring results for wastewater pollutants in each group are presented in Table 3 and Fig. 1 c. This table demonstrates significant variations in pollutant concentration levels across different cement plants and regions, with distinct concentration characteristics for typical pollutants such as heavy metals and organic compounds. These differences reflect variations in production processes and wastewater treatment efficiency among the three cement plants. pH Value: The pH values of wastewater discharged from the three cement plants ranged from 6.967 (NC2) to 7.433 (BC1), all falling within the 6–9 range required by the National Industrial Wastewater Discharge Standard. This indicates that the pH levels of the discharged wastewater are stable and will not cause acid or alkaline pollution to the receiving water bodies (Liu et al., 2024b).Chemical oxygen demand concentrations varied significantly across cement plants. ZL plants exhibited the highest concentrations at 23.333 mg/L (ZL1) and 25.333 mg/L (ZL2), followed by BC plants (20.000–20.333 mg/L). while Plant NC recorded the lowest COD levels in the first quarter (5.333 mg/L), rising to 18.667 mg/L in the second quarter. Five-day biochemical oxygen demand (BOD₅) concentrations exhibited a similar trend to COD: BC2 (8.567 mg/L) and ZL2 (7.700 mg/L) showed the highest values, while NC1 (1.600 mg/L) had the lowest. The five-day biochemical oxygen demand/chemical oxygen demand ratios for all groups ranged from 0.22 (NC1) to 0.42 (BC2), indicating that the organic matter in the wastewater was predominantly refractory organic matter. This aligns with the characteristics of wastewater generated during cement production (primarily from coal combustion and raw material processing) (Linge et al., 2024 ).The NH₃-N concentration was highest in BC2 (0.408 mg/L), followed by BC1 (0.275 mg/L), while the NH₃-N concentrations at the NC and ZL plants were relatively low (0.080 to 0.137 mg/L). Significant variations in total phosphorus (TP) concentrations were observed across cement plants: ZL Plant exhibited the highest TP levels at 0.262 mg/L (ZL1) and 0.300 mg/L (ZL2), which were 6.09 to 15.00 times higher than those at BC Plant (0.032 to 0.043 mg/L) and 13.10 to 15.00 times higher than at NC1 (0.020 mg/L). The TP concentration in NC2 (0.117 mg/L) was 4.88 times that of NC1, showing a significant upward trend. Concentration patterns vary significantly among different heavy metals. (1) As: The highest arsenic concentrations were found at the BC factory (0.527–0.717 mg/L), which was 1.28–2.05 times higher than those at the NC factory (0.350–0.413 mg/L) and ZL factory (0.383–0.520 mg/L); (2) Hg: Mercury concentrations were also highest at BC Plant (0.069–0.079 mg/L), 1.24–1.72 times higher than at NC Plant (0.046–0.056 mg/L) and ZL Plant (0.045–0.047 mg/L); (3) Pb: BC1 exhibited the highest lead concentration (0.078 mg/L), while BC2 showed only 0.006 mg/L—a 92.31% decrease compared to BC1. This reduction may result from enhanced heavy metal control measures implemented by the cement plant; (4) Cr and Cd: Concentrations of these two heavy metals were relatively low across all groups, ranging from 0.010 to 0.016 mg/L for hexavalent chromium and 0.002 to 0.004 mg/L for cadmium. No significant differences were observed between plants or across seasons (Dhokpande et al., 2024).Overall, wastewater pollutants from these three cement plants exhibit distinct site-specific and seasonal characteristics: Plant BC primarily contains high concentrations of As, Hg, and NH₃-N; Plant ZL is characterized by elevated levels of COD, BOD, and TP; while Plant NC shows relatively low concentrations of most pollutants in the first quarter, with significant increases in COD, SS, and TP during the second quarter. These monitoring results provide foundational data support for subsequent ecological risk assessments of wastewater pollutants and the development of targeted control measures. 3.3.2 Wastewater pollutant health risk assessment Based on wastewater pollutant monitoring data (Section 3.3.1), the ecological risk of 10 typical pollutants discharged in wastewater from the three target cement plants (BC, NC, ZL) during the first and second quarters of 2024 was assessed using the risk quotient (RQ) method. The RQ method is a classic screening-level ecological risk assessment tool widely used in industrial wastewater risk evaluation. It describes the potential adverse effects of pollutants on aquatic ecosystems by measuring the ratio of the Measured Environmental Concentration (MEC) to the Predicted No-Effect Concentration (PNEC) (Manyepa et al., 2024).The RQ values for each wastewater pollutant within each monitoring group (BC1, BC2, NC1, NC2, ZL1, ZL2) are shown in Table S2 . The magnitude of the RQ value directly reflects the ecological risk posed by the corresponding pollutant to the receiving water (El-Said et al., 2024 ). RQ values for different wastewater pollutants vary significantly among these three cement plants, while the ecological risk levels posed by each pollutant exhibit distinct “pollutant-specific” and “plant-specific” characteristics (Fig. 3 ).In this study, total phosphorus (TP) was the sole pollutant exhibiting high ecological risk (RQ ≥ 1), demonstrating the most pronounced risk characteristics. The RQ values for TP at ZL1 and ZL2 were 1.310 and 1.500, respectively, both reaching high-risk levels. This indicates that TP emissions from the ZL cement plant during both quarters would cause significant adverse impacts on the aquatic ecosystems of the receiving water bodies. Additionally, the TP RQ value for NC2 (0.58333) falls within the moderate risk range, while the TP RQ values for BC Plant (0.15833–0.21333) and NC1 (0.100) indicate low to moderate risk levels. The high TP risk at ZL Cement Plant aligns with the elevated TP concentration monitoring results in Section 3.3.1, potentially attributable to the high phosphorus content in raw materials used by ZL Cement Plant and the low removal efficiency of its wastewater treatment system for TP (Ryu et al., 2024 ). Heavy metals (Cr, Pb, Cd): These three heavy metals are the primary factors causing moderate ecological risk. The highest RQ value for Cr was observed in BC1 (0.500), followed by Cd in NC2 (0.35333) and Cd in BC1 (0.32667), as well as Pb in BC1 (0.390), all falling within the moderate risk range. RQ values for these heavy metals in other groups mostly ranged from 0.03 to 0.28, indicating low to moderate risk. Heavy metals exhibit bio-accumulative and persistent characteristics, meaning even long-term emissions at low concentrations may pose potential cumulative risks to aquatic food chains.(Ummalyma et al., 2024 ). Nutrients (NH 3 -N): BC2 exhibited the highest NH 3 -N RQ value (0.40833), followed by BC1 (0.275) and NC1 (0.137), all falling within the moderate risk range. NH 3 -N is a key factor contributing to water eutrophication. Although its RQ value is below 1, its combined impact with TP—particularly at the ZL Cement Plant—may further exacerbate eutrophication risks in receiving waters (Zhang et al., 2025). The comprehensive ecological risk levels of cement plants (characterized by the types and quantities of high/medium-risk pollutants) exhibit significant spatial and temporal variations. Spatial Differences (Inter-Plant Comparison): ZL Cement Plant exhibited the highest overall ecological risk, with TP remaining at high risk in both quarters, making it the key high-risk cement plant in this study. BC Cement Plant ranked second, showing medium risk for multiple pollutants (Cr, Pb, Cd, NH3-N) in the first quarter, with NH3-N maintaining medium risk in the second quarter. NC Cement Plant exhibited relatively low overall ecological risk, with only Cd (NC2) and NH3-N (NC1) showing moderate risk. No pollutants reached high-risk levels in either quarter. Time-based Variation (Seasonal Comparison Within the Same Plant): (1) BC Cement Plant: The number of moderately hazardous pollutants decreased from 6 types in Q1 (COD, NH3-N, TP, Cr, Cd) to 3 types in Q2 (COD, NH3-N, TP). The RQ values for Cr and Cd showed significant declines (Cr: 0.500 → 0.09667; Cd: 0.390 → 0.030). TP, Cd) in the second quarter. The RQ values for chromium and lead decreased significantly (chromium: 0.500 reduced to 0.09667; lead: 0.390 reduced to 0.03083), indicating a marked reduction in ecological risk from wastewater in the second quarter. This may be related to optimized heavy metal control processes at the cement plant. (2) NC Cement Plant: The number of moderately hazardous pollutants increased from two in the first quarter (NH₃-N, Cd) to four in the second quarter (COD, TP, Pb, Cd). The RQ value for TP rose from 0.100 to 0.58333, indicating an upward trend in ecological risk. This may be attributed to increased production loads and reduced wastewater treatment efficiency during the second quarter. (3) ZL Cement Plant: The type of high-risk pollutant (TP) remained unchanged, with TP's RQ value rising from 1.310 to 1.500. Meanwhile, the number of moderate-risk pollutants increased from 2 types (COD, Pb) in Q1 to 3 types (COD, Pb, NH3-N) in Q2, indicating a slight increase in ecological risk for wastewater during the second quarter. In summary, the wastewater discharged from these three cement plants poses varying degrees of ecological risk to the receiving water bodies. ZL Cement Plant, with its higher TP risk, is the primary high-risk source; BC Cement Plant presents a relatively moderate risk, primarily composed of heavy metals and NH₃-N; NC Cement Plant exhibits a relatively low risk. The seasonal variation in ecological risks from the wastewater of these three cement plants differs, influenced by production load adjustments and the efficiency of wastewater treatment processes. These findings provide targeted basis for developing subsequent wastewater pollution control and ecological risk management strategies for these plants, particularly prioritizing control of T at ZL Cement Plant and heavy metals at BC cement plant. Table 3 Summary Table of Wastewater Pollutant Concentrations Group pH COD (mg/L) BOD 5 (mg/L) NH4-N (mg/L) TP (mg/L) SS (mg/L) Cr (VI) (mg/L) Pb (mg/L) ) As (mg/L) Hg (mg/L) Cd (mg/L) BC1 7.433 20.000 6.600 0.275 0.032 16.000 0.015 0.078 0.717 0.079 0.003 BC2 7.233 20.333 8.567 0.408 0.043 10.333 0.010 0.006 0.527 0.069 0.003 NC1 7.300 5.333 1.600 0.137 0.020 9.333 0.014 0.016 0.350 0.046 0.002 NC2 6.967 18.667 5.367 0.080 0.117 14.667 0.015 0.031 0.413 0.056 0.004 ZL1 7.100 23.333 7.100 0.086 0.262 9.000 0.015 0.025 0.383 0.047 0.002 ZL2 7.100 25.333 7.700 0.090 0.300 9.333 0.016 0.032 0.520 0.045 0.002 3.4 Noise pollution risk assessment To systematically identify the primary pollution risk sources and their spatiotemporal distribution characteristics at these three target cement plants, this section integrates non-carcinogenic health risks from air pollutants, ecological risks from wastewater pollutants, and noise disturbance risks to establish a comprehensive risk assessment framework. The comprehensive risk value for each monitoring group (BC1, BC2, NC1, NC2, ZL1, ZL2) is derived by standardizing and integrating the three risk dimensions (noise, air pollution, water pollution). Radar charts (Fig. 4 ) visually illustrate risk variations. Comparisons and rankings based on two core dimensions—spatial variations between factories and seasonal variations within factories (Q1 and Q2)—aim to provide a comprehensive decision-making basis for integrated regional industrial pollution management. It should be noted that the noise risk values for all groups have been standardized to 1.000. This indicates that noise emissions from all cement plants comply with national standards (Section 3.1 ), with no risk of exceeding limits. Therefore, this value serves as the baseline reference for comprehensive risk comparison. The air pollution risk value corresponds to the HI in Section 3.2 , while the water pollution risk value corresponds to the key ecological risk feature value in Section 3.3 (derived from the RQ of primary wastewater pollutants). Significant differences in comprehensive risk levels exist among the factories, revealing a clear hierarchical distribution: ZL Cement Plant and BC Cement Plant fall into the high-risk tier, while NC Cement Plant is classified in the medium-to-low risk tier (Fig. 4 ). ZL1 (4.175) and ZL2 (5.174) ranked second and first respectively in overall risk scores across all groups. Their notable characteristic is elevated water pollution risk, with values of 1.310 (ZL1) and 1.500 (ZL2). These figures represent 3.36 to 7.69 times higher than BC Cement Plant (0.390–0.408) and 2.25 to 6.41 times higher than NC Cement Plant (0.234–0.583). Although ZL Cement Plant's air pollution risk (1.865–2.674) was lower than that of BC Cement Plant, the combined effect of its high -water pollution risk made it the cement plant with the highest overall risk in the second quarter.From the first quarter (4.175) to the second quarter (5.174), the total comprehensive risk increased by 23.92%. This growth was primarily driven by a 14.50% rise in air pollution risk (from 1.865 to 2.674) and a 14.50% increase in water pollution risk (from 1.310 to 1.500). Persistently high-water pollution risks coupled with escalating air pollution risks made the ZL cement plant a priority target for risk control in the second quarter. In summary, the comprehensive risks of these three cement plants exhibit distinct spatial and temporal variations: ZL Cement Plant faced the highest overall risk in the second quarter due to its elevated water pollution risk; BC Cement Plant, characterized by elevated air pollution risks, exhibited a declining trend in the second quarter; NC Cement Plant demonstrated the lowest overall risk but showed an upward trend during the second quarter. The ranking and classification of comprehensive risks provide regional environmental management authorities with a clear “target list.” Targeted control strategies should prioritize water pollution control at ZL Cement Plant and air pollution control at BC Cement Plant (Firdissa et al., 2024). 4. Conclusion This study systematically assessed the environmental risks associated with multi-media pollutants (noise, air, wastewater) from three cement plants (BC, NC, ZL) during the first and second quarters of 2024. Through single-factor and integrated risk assessments, key risk characteristics and spatio-temporal variations were identified, providing targeted support for regional pollution management. The main conclusions are as follows: All cement plants meet national standards for noise emissions (standardized risk value = 1.000), posing no excessive risk of disturbing residents. All cement plants pose potential non-carcinogenic health risks from air pollutants (Risk Index > 1). BC Cement Plant exhibits the highest air pollution risk (Risk Index: 2.730–3.043), primarily from NOX, PM, and TSP, which decreased by 10.29% from Q1 to Q2. ZL (Risk Index: 1.865–2.674) and NC (Risk Index: 1.671–1.972) exhibit lower air pollution risks, though ZL's risk increased in the second quarter.Significant ecological risk variations exist among wastewater sources: ZL represents a high-risk source with a TP risk ratio ranging from 1.310 to 1.500; BC exhibits moderate wastewater risks (involving heavy metals and NH₃-N); NC demonstrates the lowest Q1 water quality risk, yet its Q2 risk increased by 149.15%, primarily due to elevated TP and Pb levels. Comprehensive risks exhibit distinct spatial and temporal variations: ZL showed highest risks during Q2 (severe water pollution), BC had elevated air risks with a declining trend, while NC presented the lowest overall risks but demonstrated an upward trend during Q2. Risk ranking: ZL2 > BC1 > ZL1 > BC2 > NC2 > NC1. Targeted control measures should prioritize TP removal at ZL and NOx/PM reduction at BC. However, limitations include the relatively short monitoring period and the absence of carcinogenic risk assessment. Future studies should extend the monitoring duration, incorporate carcinogenic risk analysis, and utilize numerical modeling to investigate pollutant migration patterns, thereby providing more comprehensive decision support. Credit author statement Jie Jiang,Xin Li(First Author, these authors contributed equally to this work): Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing - Original Draft; Guanhou Chen: Data Curation, Writing - Original Draft; Bin Li: Visualization, Investigation; Rong Wang: Resources, Supervision; Limei Luo: Software, Validation; Shuai Li (Corresponding Author): Conceptualization, Funding Acquisition, Resources, Supervision, Writing - Review & Editing. Declarations Declaration of competing 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 paper. Funding Declaration There is no funding for this article. Author Contribution Jie Jiang,Xin Li(First Author, these authors contributed equally to this work): Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing - Original Draft;Guanhou Chen: Data Curation, Writing - Original Draft;Bin Li: Visualization, Investigation;Rong Wang: Resources, Supervision;Limei Luo: Software, Validation;Shuai Li (Corresponding Author): Conceptualization, Funding Acquisition, Resources, Supervision, Writing - Review & Editing. References Bărbulescu, A. & Hosen, K. (2025). Cement Industry Pollution and Its Impact on the Environment and Population Health: A Review. 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Supplementary Files image1.jpeg Abstract Graphic Supportinginformation.docx Supportinginformation.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 25 Apr, 2026 Reviewers invited by journal 27 Mar, 2026 Editor assigned by journal 18 Mar, 2026 Submission checks completed at journal 18 Mar, 2026 First submitted to journal 10 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8838504","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":614393582,"identity":"0a5e34b7-48a3-4762-9996-fb58cd4bdd6d","order_by":0,"name":"shuai li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYBAC+/sHmx9+MKipZ2NvIFbPDeZjxhIFxxL4eA4QrYUtQYLnA3OCnEQCkToYZ/cYGEgYsOWxST7eeIOhxiaaoBZmmTMGDwoMZIrZpNOKLRiOpeU2ENLCxpADtoWxTTrHTIKx4TBhLTxALRI8BsyMbZJniNQiIZGWANKS2CbBQ6QWA57DwEA2OGbMxgP0SwIxfjFgbwRG5Z8aOfn2wxtvfKixIawFRTvRUYOkhVQdo2AUjIJRMDIAAPsPOkZqS/NQAAAAAElFTkSuQmCC","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":true,"prefix":"","firstName":"shuai","middleName":"","lastName":"li","suffix":""},{"id":614393583,"identity":"fd79d374-9851-49c0-90e1-047a61208c81","order_by":1,"name":"jie jiang","email":"","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"jie","middleName":"","lastName":"jiang","suffix":""},{"id":614393584,"identity":"ff242504-cbb4-4859-a293-bb857d56d1ee","order_by":2,"name":"xin li","email":"","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"xin","middleName":"","lastName":"li","suffix":""},{"id":614393585,"identity":"e9287ddc-f107-49fb-b222-5630a2726b70","order_by":3,"name":"guanhou chen","email":"","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"guanhou","middleName":"","lastName":"chen","suffix":""},{"id":614393586,"identity":"6ea5c9f9-32bc-48ee-a72c-e478daded21d","order_by":4,"name":"bin li","email":"","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"bin","middleName":"","lastName":"li","suffix":""},{"id":614393587,"identity":"287d5c12-0878-46a3-957b-cbdb08d266b4","order_by":5,"name":"rong wang","email":"","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"rong","middleName":"","lastName":"wang","suffix":""},{"id":614393588,"identity":"8ccb6e4d-738f-43b9-bff9-a42858117015","order_by":6,"name":"limei luo","email":"","orcid":"","institution":"Xipu Technology (Chengdu) Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"limei","middleName":"","lastName":"luo","suffix":""}],"badges":[],"createdAt":"2026-02-10 08:39:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8838504/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8838504/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105821401,"identity":"833af15d-b61b-47dc-a5b7-f58b2e9703df","added_by":"auto","created_at":"2026-03-31 13:17:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2922446,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot of pollutant concentration statistics for the first and two quarters of operation of three cement plants. (a) noise; (b) air pollutants; (c) water pollutants. For each picture, two representative pollutants have been selected.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/716287f264e0e1cdcaae6b3a.jpeg"},{"id":105821402,"identity":"f43f62f6-619d-4d7f-a58f-0dca8b44e256","added_by":"auto","created_at":"2026-03-31 13:17:42","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1768744,"visible":true,"origin":"","legend":"\u003cp\u003eComparison chart of health risks from exhaust gas.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/49037a54595a460ba5c7767a.jpeg"},{"id":105821404,"identity":"0da6bb6d-002b-4ea8-a7a5-9f1fd0807337","added_by":"auto","created_at":"2026-03-31 13:17:42","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1685993,"visible":true,"origin":"","legend":"\u003cp\u003eWastewater ecological risk quotient heat map.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/de4eaf78168e898b73ac51d3.jpeg"},{"id":105904693,"identity":"8cb521cf-a076-4454-a0cc-8ff4ec07afdf","added_by":"auto","created_at":"2026-04-01 10:10:16","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8826559,"visible":true,"origin":"","legend":"\u003cp\u003eComparison radar chart of comprehensive risks for the first and second quarters of the three cement plants.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/359a3fb67418899145653a09.jpeg"},{"id":106959677,"identity":"1f44829a-2a4e-40ae-b461-f7d3875c4d92","added_by":"auto","created_at":"2026-04-15 09:13:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16200229,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/8aff6fc9-e680-425b-94a8-a5cf54f84e7a.pdf"},{"id":106723852,"identity":"614222c9-a1e6-48bb-b1f3-cbcfd08226df","added_by":"auto","created_at":"2026-04-12 18:16:54","extension":"jpeg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11803313,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbstract Graphic\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/99b9ca081e7978f93204781c.jpeg"},{"id":105821403,"identity":"8e3e7ab0-3221-4ecc-8a4d-5aef795fd4f9","added_by":"auto","created_at":"2026-03-31 13:17:42","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":21188,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/5239acb259c47a5e32fc05e6.docx"},{"id":105821407,"identity":"d7435939-7db8-4473-a5f1-da0d55b17021","added_by":"auto","created_at":"2026-03-31 13:17:42","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":21188,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8838504/v1/ac644c93e47a526d798620ad.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Monitoring-Based Comprehensive Environmental Risk Assessment of Multi-Medium Pollutants and Spatiotemporal Differences in Three Typical Cement Plants","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe cement industry serves as a vital pillar of the global construction sector, playing an irreplaceable role in urbanization and infrastructure development (Jena et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, cement production involves complex processes such as raw material calcination, clinker grinding, and fuel combustion, inevitably generating multiple types of pollutants. These include noise, air pollutants (such as nitrogen oxides, particulate matter, and total suspended solids), and wastewater contaminants (such as heavy metals, total phosphorus, and chemical oxygen demand). These pollutants trigger a series of environmental impacts: air pollutants pose non-carcinogenic health risks to surrounding populations, wastewater pollutants create ecological risks to receiving water bodies, and persistent noise emissions may cause disturbance to residents (Salazar-Rojas et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). As global environmental regulations become increasingly stringent, the comprehensive environmental risk assessment of multi-media pollutants from cement plants has emerged as a key research focus in industrial environmental management (Bărbulescu and Hosen, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch on pollution from cement plants has achieved certain progress. Regarding air pollution, most studies have focused on the concentration characteristics of particulate matter or nitrogen oxides and their potential health risks, confirming their adverse effects on the respiratory system (Kane et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Concerning wastewater pollution, relevant research has primarily concentrated on removal technologies for heavy metals or nutrients, with less attention paid to ecological risk characterization based on the risk quotient (RQ). Regarding noise pollution, research has largely been confined to monitoring emission levels, lacking integrated consideration of noise risks within the comprehensive environmental risk framework for cement plants (Rawat et al., 2025).\u003c/p\u003e \u003cp\u003eIt is worth noting that current research exhibits significant shortcomings: (1) Most studies focus solely on pollution assessments for single media, neglecting the synergistic effects of combined risks from multiple pollutants (noise-air-water). This approach fails to comprehensively reflect the overall environmental impact of cement plants; (2) Few studies address temporal variations in pollution risks (e.g., seasonal changes), making it difficult to clarify the dynamic patterns of risk driven by production adjustments and meteorological factors; (3) Targeted research on integrated risk ranking and key risk source identification for multiple cement plants within the same region is insufficient, limiting the formulation of precise regional pollution control strategies (Nwogu et al., 2025).\u003c/p\u003e \u003cp\u003eTo address these gaps, this study selected three representative cement plants (BC, NC, ZL) as research subjects and systematically assessed the environmental risks of multi-media pollutants during the first and second quarters of 2024. The specific research objectives are: (1) to clarify the emission levels of noise, air pollutants, and wastewater pollutants from these three cement plants and their single-factor risk characteristics; (2) to analyze the spatiotemporal differences in comprehensive environmental risks among different cement plants and across different quarters; (3) to identify key risk sources and propose targeted pollution control strategies. This study aims to establish a multidimensional environmental risk assessment framework for cement plants, provide scientific basis for integrated regional industrial pollution management, and offer reference for optimizing pollution control measures in the cement industry.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Overview of study area and target cement plant\u003c/h2\u003e \u003cp\u003eThe study area encompasses Mianyang City and Nanchong City, located in the northwest and northeast of the Sichuan Basin in southwest China, respectively. Mianyang City (30\u0026deg;42\u0026prime;\u0026ndash;31\u0026deg;29\u0026prime; N, 103\u0026deg;45\u0026prime;\u0026ndash;105\u0026deg;43\u0026prime; E) has an annual average temperature of 16.3\u0026ndash;17.7\u0026deg;C and annual average precipitation of 825\u0026ndash;1417 mm, primarily concentrated during the summer months (June to August)(Liu et al., 2024a). Nanchong City (30\u0026deg;35\u0026prime; N\u0026thinsp;\u0026minus;\u0026thinsp;31\u0026deg;51\u0026prime; N, 105\u0026deg;27\u0026prime; E\u0026thinsp;\u0026minus;\u0026thinsp;106\u0026deg;58\u0026prime; E) has an annual average temperature of 17.4\u0026deg;C and annual precipitation ranging from 980 to 1150 mm. Both cities are major industrial hubs in Sichuan Province, with cement production serving as a vital pillar industry supporting local infrastructure development (Zhang et al., 2023). However, the intensive discharge of multiple pollutants (exhaust gases, wastewater, and noise) from cement plants in these regions poses potential threats to the local ecological environment and human health.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data source and monitoring methods\u003c/h2\u003e \u003cp\u003eAll environmental monitoring data in this study were obtained from supervisory monitoring conducted by Xipu Technology Co., Ltd. during the first and second quarters of 2024. This monitoring complied with the technical requirements of national environmental monitoring standards. Monitoring indicators covered three environmental media: exhaust gases, wastewater, and noise. Monitoring frequency, monitoring point layout, and technical specifications were strictly implemented in accordance with relevant national and industry standards.\u003c/p\u003e \u003cp\u003eWaste gas monitoring: Key pollutants monitored include total suspended particulates, ammonia, hydrogen sulfide, odor concentration, particulate matter, sulfur dioxide, nitrogen oxides, fluorides, and dioxins. Monitoring employs a continuous automatic monitoring system (Model: TH-2000B) with detection limits as follows: total suspended particulates (TSP): 0.007 mg/m\u0026sup3;, ammonia (NH\u003csub\u003e3\u003c/sub\u003e): 0.01 mg/m\u0026sup3;, hydrogen sulfide (H\u003csub\u003e2\u003c/sub\u003eS): 0.001 mg/m\u0026sup3;, particulate matter (PM): 1.0 mg/m\u0026sup3;, SO\u003csub\u003e2\u003c/sub\u003e: 3 mg/m\u0026sup3;, NO\u003csub\u003eX\u003c/sub\u003e: 3 mg/m\u0026sup3;. This monitoring complies with the Technical Specification for Monitoring of Waste Gas from Fixed Pollution Sources (HJ/T 75-2017). For each cement plant, four monitoring points will be established at the plant boundary, including one upwind point and three downwind points (downwind points arranged along the prevailing wind direction of the study area). Monitoring will be conducted continuously for 24 hours daily, with data recorded at one-hour intervals. Fifteen days of valid monitoring data will be collected each quarter (excluding days with extreme weather conditions such as heavy rain and strong winds).\u003c/p\u003e \u003cp\u003eWastewater: The monitored parameters include pH, chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD\u003csub\u003e5\u003c/sub\u003e), suspended solids (SS), ammonia nitrogen (NH\u003csub\u003e3\u003c/sub\u003e-N), total phosphorus (TP), and specific heavy metals (hexavalent chromium (Cr), lead (Pb), cadmium (Cd), mercury (Hg), arsenic (As)). pH was measured using a pH meter (PHBJ-260); COD was determined via the potassium dichromate digestion method (detection limit: 4 mg/L); SS was measured by gravimetric analysis (detection limit: 4 mg/L); heavy metals were analyzed using atomic fluorescence spectrophotometry/ atomic absorption spectrophotometer (AFS-8500/TAS-990AFG), with detection limits of 0.004 mg/L for chromium, 0.3 \u0026micro;g/L for arsenic, 0.001 mg/L for cadmium, and 0.004 \u0026micro;g/L for mercury. Monitoring procedures followed the guidelines outlined in \u0026ldquo;Water Quality - Sampling and Sample Preparation for Physical and Chemical Analysis\u0026rdquo; (GB/T 12998\u0026thinsp;\u0026minus;\u0026thinsp;2008). A monitoring point is established at the final discharge outlet of each factory's wastewater treatment system. Samples are collected every 3 days, with 3 parallel samples taken each time. A total of 15 valid sample sets is obtained each quarter.\u003c/p\u003e \u003cp\u003eNoise: During daytime (06:00\u0026ndash;22:00) and nighttime (22:00\u0026ndash;06:00), the equivalent continuous A-weighted sound level (Leq) at the factory boundary was monitored using a sound level meter (Model: AWA5688). The meter has a measurement range of 30\u0026ndash;130 dB(A) and an accuracy of \u0026plusmn;\u0026thinsp;1 dB(A). Monitoring activities were conducted in accordance with the \u0026ldquo;Specification for Noise Measurement at Boundaries of Industrial Enterprises\u0026rdquo; (GB/T 12348\u0026thinsp;\u0026minus;\u0026thinsp;2008). Six monitoring points were evenly distributed along the perimeter of each factory. Each point was monitored for 10 minutes, with the average value serving as the Leq value for that point. Monitoring was conducted every 7 days, yielding 5 valid monitoring periods per quarter.\u003c/p\u003e \u003cp\u003eAll monitoring data have been aggregated and verified to exclude invalid data (e.g., data with obvious measurement errors or affected by extreme weather conditions). Aggregated statistical information for noise, exhaust emissions, and wastewater pollutant monitoring data is presented in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Risk Assessment Framework and Methodology\u003c/h2\u003e \u003cp\u003eThis study employs a screening-level risk assessment framework characterized by conservative assumptions and simplified calculation methods, suitable for identifying potential high-risk pollutants and sources under conditions of limited data. The framework comprises four core steps: hazard identification, exposure assessment, toxicity assessment, and risk characterization.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Noise pollution risk assessment\u003c/h2\u003e \u003cp\u003eNoise Disturbance Risk Assessment The risk of noise disturbance is assessed using the threshold comparison method, referencing the Environmental Noise Quality Standard (GB 3096\u0026thinsp;\u0026minus;\u0026thinsp;2008). The boundaries of the three cement plants are located within Category 2 zones (mixed residential, commercial, and industrial areas), where the daytime standard limit is Leq 60 dB(A) and the nighttime limit is 50 dB(A). The calculation method for the degree of noise exceedance is as follows: Degree of Exceedance (dB(A)) = Measured Leq - Standard Limit (Easton et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Waste gas risk assessment\u003c/h2\u003e \u003cp\u003eReference concentration (RfC, milligrams per cubic meter) represents the pollutant concentration that poses no adverse health effects even with long-term exposure, serving as a toxicity indicator. Reference concentration values for PM₁₀ and NO₂ were obtained from China's Technical Guidelines for Environmental Health Risk Assessment of Pollutants. For instance, the reference concentration for TSP and NH₃ is 0.002 mg/m\u0026sup3;, for H₂S it is 0.06 mg/m\u0026sup3;, and for malodorous gases it is 20 mg/m\u0026sup3;.\u003c/p\u003e \u003cp\u003eThe Hazard Quotient (HQ) is used to describe the non-carcinogenic risk of a single pollutant, while the Hazard Index (HI) is used to describe the combined non-carcinogenic risk of multiple pollutants. Their calculation formulas are as follows:\u003c/p\u003e \u003cp\u003eHQ\u0026thinsp;=\u0026thinsp;C / RfC\u003c/p\u003e \u003cp\u003eHI\u0026thinsp;=\u0026thinsp;ΣHQ\u003c/p\u003e \u003cp\u003eAccording to the U.S. Environmental Protection Agency's guidance principles, if the HI is less than 1, it indicates that the non-carcinogenic risk is acceptable; whereas if the HI is greater than or equal to 1, it indicates that the risk warrants attention and requires a more detailed assessment (Qin et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2026\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Wastewater risk assessment\u003c/h2\u003e \u003cp\u003eThe ecological risk of wastewater pollutants was assessed using the risk quotient (RQ) method, which is widely applied in screening-level ecological risk assessments. The risk quotient is calculated as the ratio of the measured environmental concentration (MEC) to the predicted no-effect concentration (PNEC):\u003c/p\u003e \u003cp\u003eRQ\u0026thinsp;=\u0026thinsp;MEC / PNEC\u003c/p\u003e \u003cp\u003eMEC (mg/L) refers to the maximum detected concentration of pollutants in wastewater from each facility during the corresponding quarter; PNEC (milligrams per liter) denotes the concentration at which no adverse ecological effects are predicted to occur. PNEC values for different pollutants were obtained from the European Chemicals Agency (ECHA) risk assessment reports and China's Surface Water Quality Standards.Based on the RQ value, ecological risks are categorized into three levels: low risk (RQ\u0026thinsp;\u0026lt;\u0026thinsp;0.1), moderate risk (0.1\u0026thinsp;\u0026le;\u0026thinsp;RQ\u0026thinsp;\u0026lt;\u0026thinsp;1), and high risk (RQ\u0026thinsp;\u0026ge;\u0026thinsp;1) (Sim et al., 2024).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Noise pollution risk assessment\u003c/h2\u003e \u003cp\u003eNoise pollution generated by cement plants directly impacts the living environment and physical and mental health of residents surrounding the facilities (Razai et al., 2025). This section employs a threshold comparison method based on national environmental quality standards to assess the noise disturbance risk for three target cement plants (BC, NC, ZL) during the first and second quarters of 2024 (referred to as BC1, BC2, NC1, NC2, ZL1, and ZL2, respectively).\u003c/p\u003e \u003cp\u003eThe specific results of daytime and nighttime noise monitoring at each factory boundary are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea. As indicated in the table, all measured Leq values for the three factories during both quarters remained below the corresponding standard limits, with no instances of noise pollution exceeding the threshold detected (Pradeep and Nagendra, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Specifically, for daytime noise: Measurements ranged from 47.367 dB(A) (NC2) to 56.733 dB(A) (NC1), all below the 60 dB(A) standard limit. The maximum deviation from the standard limit was 12.633 dB(A) (NC2), and the minimum deviation was 3.267 dB(A) (NC1). For nighttime noise: measured values ranged from 41.467 dB(A) (ZL2) to 49.800 dB(A) (NC1), all below the 50 dB(A) standard limit. Among these, NC1's nighttime noise was closest to the standard limit, with a difference of only 0.200 dB(A), while ZL2 showed the largest deviation, with a gap of 8.533 dB(A) from the standard limit. All noise risks in the monitored groups of this study were classified as \u0026ldquo;no risk.\u0026rdquo; Among them, although the NC1 group's nighttime noise levels came closest to the standard limit, the measured values remained below the standard threshold, thus posing no disturbance risk to residents. The ZL2 group exhibited the lowest daytime and nighttime noise levels across all groups, indicating that ZL Cement Plant achieved relatively optimal noise control performance during the second quarter (Quader et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, noise emissions from these three cement plants during the first and second quarters of 2024 complied with national environmental quality standards, posing no risk of noise disturbance to residents. From the perspective of temporal and spatial variation, NC Plant exhibited the highest daytime noise levels across all categories during the first quarter, while nighttime noise levels remained generally low at all plants. Noise levels at each plant showed a downward trend in the second quarter compared to the first quarter, potentially attributable to production process optimization and enhanced noise control measures implemented by the plants.(Gao and Ye, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Noise Pollution\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaytime noise (dB)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard value (dB)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNight noise (dB)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard value (dB)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Atmospheric pollution risk assessment\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Atmospheric Pollutant Monitoring Level Overview\u003c/h2\u003e \u003cp\u003eAir pollutants emitted during cement production\u0026mdash;such as particulate matter, sulfur oxides, and nitrogen oxides\u0026mdash;are significant factors affecting regional air quality and human health (Yan et al., 2025).Detailed monitoring results for each group of air pollutants are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb. As evident from this table, concentration levels of various pollutants exhibit significant differences between different cement plants and regions, with characteristic pollutants displaying distinct concentration patterns:\u003c/p\u003e \u003cp\u003eParticulate Matter Pollutants (TSP and PM): TSP concentrations varied significantly across cement plants, with the highest levels observed at BC Plant (0.494\u0026ndash;0.557 mg/m\u0026sup3;), which was 1.86 times higher than NC Plant (0.238\u0026ndash;0.262 mg/m\u0026sup3;) and 1.87 times higher than ZL Plant (0.263\u0026ndash;0.269 mg/m\u0026sup3;). \u0026minus;\u0026thinsp;0.262 mg/m\u0026sup3;) and ZL Plant (0.263\u0026ndash;0.269 mg/m\u0026sup3;). For PM, ZL1 exhibited the highest concentration (6.800 mg/m\u0026sup3;), followed by BC1 (5.600 mg/m\u0026sup3;), while NC2 recorded the lowest concentration (3.867 mg/m\u0026sup3;). From a seasonal variation perspective, TSP concentrations at BC plant decreased by 11.31% from Q1 to Q2, while PM concentrations decreased by 11.30%. At ZL plant, PM concentrations dropped by 29.41% from Q1 to Q2, showing a significant downward trend.\u003c/p\u003e \u003cp\u003eGaseous pollutants (NH\u003csub\u003e3\u003c/sub\u003e, H\u003csub\u003e2\u003c/sub\u003eS, SO\u003csub\u003e2\u003c/sub\u003e, NO\u003csub\u003eX\u003c/sub\u003e, fluorides): H\u003csub\u003e2\u003c/sub\u003eS concentrations were relatively low across all groups, ranging from 0.002 to 0.004 mg/m\u0026sup3;, with no significant differences observed between plantations or seasons. NH\u003csub\u003e3\u003c/sub\u003e concentrations peaked in BC1 (0.490 mg/m\u0026sup3;) and were lowest in ZL1 (0.060 mg/m\u0026sup3;). SO\u003csub\u003e2\u003c/sub\u003e exhibited the most pronounced plantation variation, with ZL Plant concentrations (4.667\u0026ndash;7.667 mg/m\u0026sup3;) being 3.34\u0026ndash;5.61 times higher than those at BC Plant (1.367\u0026ndash;1.400 mg/m\u0026sup3;) and NC Plant (1.333\u0026ndash;1.433 mg/m\u0026sup3;). while ZL1's SO\u003csub\u003e2\u003c/sub\u003e concentration was 64.30% higher than ZL2's. NO\u003csub\u003eX\u003c/sub\u003e concentrations peaked at BC Plant (69.667\u0026ndash;82.667 mg/m\u0026sup3;), followed by NC Plant (44.667\u0026ndash;56.667 mg/m\u0026sup3;), with ZL Plant recording the lowest levels in Q1 (22.333 mg/m\u0026sup3;); NOx concentrations at the BC plant decreased by 15.73% from Q1 to Q2, showing a downward trend. Fluoride concentrations were extremely high in ZL2 (0.822 mg/m\u0026sup3;), 2.97 to 27.40 times higher than in other groups.\u003c/p\u003e \u003cp\u003eOdor and polychlorodibenzo-p-dioxins (PCDDs): Odor concentrations were highest in the BC2 and ZL2 groups (both at 13 mg/m\u0026sup3;) and lowest in the NC1 group (7.067 mg/m\u0026sup3;). PCDD concentrations were relatively low across all groups, ranging from 0.003 to 0.013 TEQ/m\u003csup\u003e3\u003c/sup\u003e, with the highest concentration observed in the BC2 group (0.013 TEQ/m\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eOverall, the concentrations of air pollutants at these three cement plants exhibit distinct site-specific and seasonal characteristics: BC Plant primarily features high concentrations of TSP and NOX, ZL Plant predominantly shows elevated levels of SO2 and fluorides (especially at ZL2), while NC Plant generally has relatively lower concentrations for most pollutants. From a seasonal perspective, most pollutants at BC and ZL plants showed a decreasing trend from the first to the second quarter. This may be attributed to production process optimization, enhanced end-of-pipe treatment facilities, and changes in meteorological conditions (for instance, increased precipitation and improved dispersion conditions in the second quarter)(Feng et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The monitoring levels of the aforementioned air pollutants provide foundational data support for subsequent health risk assessments of key pollutants(Moffa et al., 2025).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Atmospheric Pollutant Health Risk Assessment\u003c/h2\u003e \u003cp\u003eBased on air pollutant monitoring data (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, we assessed the non-carcinogenic health risks for the first and second quarters of 2024 at three cement plants (BC, NC, ZL) using the Hazard Quotient (HQ) and Hazard Index (HI) models recommended by the U.S. Environmental Protection Agency (EPA). HQ describes the non-carcinogenic risk for a single pollutant, while HI (the sum of the hazard quotients for all pollutants) reflects the combined non-carcinogenic risk from mixed pollutants (He et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Concentration values of major air pollutants and the comprehensive health index values for each monitoring group (BC1, BC2, NC1, NC2, ZL1, ZL2) are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAs shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, the health risk values for different air pollutants vary significantly among these three cement plants, and each pollutant contributes differently to the overall health risk. NO\u003csub\u003eX\u003c/sub\u003e: As the primary risk factor at the BC factory, its concentration ratios in BC1 and BC2 were 0.827 and 0.697 respectively, both ranking highest within their respective groups. Although the concentration ratios of NO\u003csub\u003eX\u003c/sub\u003e at NC and ZL plants (0.447\u0026ndash;0.567 and 0.223\u0026ndash;0.517) were lower than those at BC plant, they still ranked among the top three pollutants by concentration ratio within each group. This is because NOX from cement production processes (such as calcination) exhibits strong respiratory toxicity, with long-term exposure causing damage to the respiratory and cardiovascular systems (Nomura et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePM and TSP: These two particulate pollutants represent significant risk factors across all three factories. At the ZL1 factory, PM exhibited the highest HQ value (0.680), followed by BC1 (0.560); At the BC plant, the HQ values for TSP (0.494\u0026ndash;0.557) were significantly higher than those at the NC plant (0.238\u0026ndash;0.262) and the ZL plant (0.263\u0026ndash;0.269), consistent with the particulate matter monitoring concentration characteristics described in Section \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e3.2.1\u003c/span\u003e. Particulate matter can penetrate deep into the respiratory tract and even enter the bloodstream, triggering chronic diseases such as asthma and pulmonary fibrosis (Wang et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOdor: In BC2 and ZL2, the HQ values for odor are relatively high (both 0.650), 1.84 times higher than the value in NC1 (0.353, the lowest value). These odor pollutants (primarily volatile organic compounds and ammonia) cause sensory discomfort and psychological stress, and certain components possess potential toxic effects (Wu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).Other Pollutants: The hazard index values for H₂S, SO₂, fluorides, and PCDDs were relatively low across all groups, with most values below 0.3. This indicates their respective non-carcinogenic risks are negligible. However, it should be noted that the hazard index value for fluoride in the ZL2 group was 0.274, which was 2.49 to 27.40 times higher than in other groups. This indicates that the ZL plant should focus on controlling fluoride emissions during the second quarter.\u003c/p\u003e \u003cp\u003eThe overall non-carcinogenic risk level (denoted as HI) for each group exhibits significant spatial and temporal variations. Spatial differences (Comparisons Among Cement Plants): The BC plant exhibits the highest overall health risk, with HI values of 3.063 (BC1) and 2.804 (BC2), representing 1.49 to 1.76 times higher than the NC plant (1.738\u0026ndash;2.049), which has the lowest risk among the three cement plants. ZL Plant's HI values of 1.940 (ZL1) and 2.689 (ZL2) fall between those of BC and NC plants. This spatial variation primarily stems from the combined effects of high NOx, TSP, and PM concentrations at BC Plant, collectively contributing to its highest overall risk (Wang et al., 2025).\u003c/p\u003e \u003cp\u003eTime difference (Seasonal comparison with cement plant): (1) BC Plant: From Q1 to Q2, HI decreased by 8.46%, associated with declines in HQ values for TSP, NOX, and PM (consistent with the decreasing trend in their monitored concentrations in Section \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e3.2.1\u003c/span\u003e); (2) NC Plant: From Q1 to Q2, HI increased by 17.90%, primarily due to higher HQ values for NH₃, H₂S, odor, and NOₓ; (3) ZL Plant: From Q1 to Q2, HI increased by 38.61%, primarily due to significant increases in fluoride HQ values (from 0.011 to 0.274) and odor HQ values (from 0.400 to 0.650), along with an increase in NO\u003csub\u003eX\u003c/sub\u003e HQ values. Seasonal variations in HI may result from the combined effects of production load adjustments, operational efficiency of end-of-pipe treatment facilities, and meteorological conditions (such as higher temperatures in the second quarter intensifying photochemical reactions, which may enhance the toxicity of certain pollutants) (Taha et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRisk Level Assessment: During Q1 and Q2, all HI values for these three plants exceeded 1 (ranging from 1.738 to 3.063). This indicates that the combined air pollutants emitted by these cement plants pose potential non-carcinogenic health risks to exposed populations in the surrounding areas. Among them, BC1 presents the highest risk (HI\u0026thinsp;=\u0026thinsp;3.063) and requires priority attention and implementation of risk mitigation measures(Ciarlantini et al., 2025).\u003c/p\u003e \u003cp\u003eIn summary, the air pollutants emitted by these three cement plants pose significant non-carcinogenic health risks, with Plant BC being the primary risk source and NO\u003csub\u003eX\u003c/sub\u003e, PM, and TSP being the main risk factors. The seasonal variations in health risks differ among the plants, influenced by multiple factors including production patterns and meteorological conditions. These findings provide targeted evidence for developing subsequent air pollution control and health risk management strategies for these three cement plants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary Table of Atmospheric Pollutant Concentrations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSP\u003c/p\u003e \u003cp\u003e(mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eS (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOdor concentration (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePM (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSO\u003csub\u003e2\u003c/sub\u003e (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNO\u003csub\u003eX\u003c/sub\u003e (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eFluoride (mg/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePCDDs (TEQ/m3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e82.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e69.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.804\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e44.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.738\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e56.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Wastewater pollution risk assessment\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Wastewater pollutant monitoring level overview\u003c/h2\u003e \u003cp\u003eWastewater discharged from cement production processes contains various pollutants (such as organic matter, nutrients, and heavy metals). If not properly treated, it may pose a potential threat to the water quality and aquatic ecosystems of receiving water bodies (Bi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).Detailed monitoring results for wastewater pollutants in each group are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec. This table demonstrates significant variations in pollutant concentration levels across different cement plants and regions, with distinct concentration characteristics for typical pollutants such as heavy metals and organic compounds. These differences reflect variations in production processes and wastewater treatment efficiency among the three cement plants. pH Value: The pH values of wastewater discharged from the three cement plants ranged from 6.967 (NC2) to 7.433 (BC1), all falling within the 6\u0026ndash;9 range required by the National Industrial Wastewater Discharge Standard. This indicates that the pH levels of the discharged wastewater are stable and will not cause acid or alkaline pollution to the receiving water bodies (Liu et al., 2024b).Chemical oxygen demand concentrations varied significantly across cement plants. ZL plants exhibited the highest concentrations at 23.333 mg/L (ZL1) and 25.333 mg/L (ZL2), followed by BC plants (20.000\u0026ndash;20.333 mg/L). while Plant NC recorded the lowest COD levels in the first quarter (5.333 mg/L), rising to 18.667 mg/L in the second quarter. Five-day biochemical oxygen demand (BOD₅) concentrations exhibited a similar trend to COD: BC2 (8.567 mg/L) and ZL2 (7.700 mg/L) showed the highest values, while NC1 (1.600 mg/L) had the lowest. The five-day biochemical oxygen demand/chemical oxygen demand ratios for all groups ranged from 0.22 (NC1) to 0.42 (BC2), indicating that the organic matter in the wastewater was predominantly refractory organic matter. This aligns with the characteristics of wastewater generated during cement production (primarily from coal combustion and raw material processing) (Linge et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).The NH₃-N concentration was highest in BC2 (0.408 mg/L), followed by BC1 (0.275 mg/L), while the NH₃-N concentrations at the NC and ZL plants were relatively low (0.080 to 0.137 mg/L). Significant variations in total phosphorus (TP) concentrations were observed across cement plants: ZL Plant exhibited the highest TP levels at 0.262 mg/L (ZL1) and 0.300 mg/L (ZL2), which were 6.09 to 15.00 times higher than those at BC Plant (0.032 to 0.043 mg/L) and 13.10 to 15.00 times higher than at NC1 (0.020 mg/L). The TP concentration in NC2 (0.117 mg/L) was 4.88 times that of NC1, showing a significant upward trend.\u003c/p\u003e \u003cp\u003eConcentration patterns vary significantly among different heavy metals. (1) As: The highest arsenic concentrations were found at the BC factory (0.527\u0026ndash;0.717 mg/L), which was 1.28\u0026ndash;2.05 times higher than those at the NC factory (0.350\u0026ndash;0.413 mg/L) and ZL factory (0.383\u0026ndash;0.520 mg/L); (2) Hg: Mercury concentrations were also highest at BC Plant (0.069\u0026ndash;0.079 mg/L), 1.24\u0026ndash;1.72 times higher than at NC Plant (0.046\u0026ndash;0.056 mg/L) and ZL Plant (0.045\u0026ndash;0.047 mg/L); (3) Pb: BC1 exhibited the highest lead concentration (0.078 mg/L), while BC2 showed only 0.006 mg/L\u0026mdash;a 92.31% decrease compared to BC1. This reduction may result from enhanced heavy metal control measures implemented by the cement plant; (4) Cr and Cd: Concentrations of these two heavy metals were relatively low across all groups, ranging from 0.010 to 0.016 mg/L for hexavalent chromium and 0.002 to 0.004 mg/L for cadmium. No significant differences were observed between plants or across seasons (Dhokpande et al., 2024).Overall, wastewater pollutants from these three cement plants exhibit distinct site-specific and seasonal characteristics: Plant BC primarily contains high concentrations of As, Hg, and NH₃-N; Plant ZL is characterized by elevated levels of COD, BOD, and TP; while Plant NC shows relatively low concentrations of most pollutants in the first quarter, with significant increases in COD, SS, and TP during the second quarter. These monitoring results provide foundational data support for subsequent ecological risk assessments of wastewater pollutants and the development of targeted control measures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Wastewater pollutant health risk assessment\u003c/h2\u003e \u003cp\u003eBased on wastewater pollutant monitoring data (Section 3.3.1), the ecological risk of 10 typical pollutants discharged in wastewater from the three target cement plants (BC, NC, ZL) during the first and second quarters of 2024 was assessed using the risk quotient (RQ) method. The RQ method is a classic screening-level ecological risk assessment tool widely used in industrial wastewater risk evaluation. It describes the potential adverse effects of pollutants on aquatic ecosystems by measuring the ratio of the Measured Environmental Concentration (MEC) to the Predicted No-Effect Concentration (PNEC) (Manyepa et al., 2024).The RQ values for each wastewater pollutant within each monitoring group (BC1, BC2, NC1, NC2, ZL1, ZL2) are shown in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. The magnitude of the RQ value directly reflects the ecological risk posed by the corresponding pollutant to the receiving water (El-Said et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRQ values for different wastewater pollutants vary significantly among these three cement plants, while the ecological risk levels posed by each pollutant exhibit distinct \u0026ldquo;pollutant-specific\u0026rdquo; and \u0026ldquo;plant-specific\u0026rdquo; characteristics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).In this study, total phosphorus (TP) was the sole pollutant exhibiting high ecological risk (RQ\u0026thinsp;\u0026ge;\u0026thinsp;1), demonstrating the most pronounced risk characteristics. The RQ values for TP at ZL1 and ZL2 were 1.310 and 1.500, respectively, both reaching high-risk levels. This indicates that TP emissions from the ZL cement plant during both quarters would cause significant adverse impacts on the aquatic ecosystems of the receiving water bodies. Additionally, the TP RQ value for NC2 (0.58333) falls within the moderate risk range, while the TP RQ values for BC Plant (0.15833\u0026ndash;0.21333) and NC1 (0.100) indicate low to moderate risk levels. The high TP risk at ZL Cement Plant aligns with the elevated TP concentration monitoring results in Section 3.3.1, potentially attributable to the high phosphorus content in raw materials used by ZL Cement Plant and the low removal efficiency of its wastewater treatment system for TP (Ryu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeavy metals (Cr, Pb, Cd): These three heavy metals are the primary factors causing moderate ecological risk. The highest RQ value for Cr was observed in BC1 (0.500), followed by Cd in NC2 (0.35333) and Cd in BC1 (0.32667), as well as Pb in BC1 (0.390), all falling within the moderate risk range. RQ values for these heavy metals in other groups mostly ranged from 0.03 to 0.28, indicating low to moderate risk. Heavy metals exhibit bio-accumulative and persistent characteristics, meaning even long-term emissions at low concentrations may pose potential cumulative risks to aquatic food chains.(Ummalyma et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Nutrients (NH\u003csub\u003e3\u003c/sub\u003e-N): BC2 exhibited the highest NH\u003csub\u003e3\u003c/sub\u003e-N RQ value (0.40833), followed by BC1 (0.275) and NC1 (0.137), all falling within the moderate risk range. NH\u003csub\u003e3\u003c/sub\u003e-N is a key factor contributing to water eutrophication. Although its RQ value is below 1, its combined impact with TP\u0026mdash;particularly at the ZL Cement Plant\u0026mdash;may further exacerbate eutrophication risks in receiving waters (Zhang et al., 2025).\u003c/p\u003e \u003cp\u003eThe comprehensive ecological risk levels of cement plants (characterized by the types and quantities of high/medium-risk pollutants) exhibit significant spatial and temporal variations. Spatial Differences (Inter-Plant Comparison): ZL Cement Plant exhibited the highest overall ecological risk, with TP remaining at high risk in both quarters, making it the key high-risk cement plant in this study. BC Cement Plant ranked second, showing medium risk for multiple pollutants (Cr, Pb, Cd, NH3-N) in the first quarter, with NH3-N maintaining medium risk in the second quarter. NC Cement Plant exhibited relatively low overall ecological risk, with only Cd (NC2) and NH3-N (NC1) showing moderate risk. No pollutants reached high-risk levels in either quarter.\u003c/p\u003e \u003cp\u003eTime-based Variation (Seasonal Comparison Within the Same Plant): (1) BC Cement Plant: The number of moderately hazardous pollutants decreased from 6 types in Q1 (COD, NH3-N, TP, Cr, Cd) to 3 types in Q2 (COD, NH3-N, TP). The RQ values for Cr and Cd showed significant declines (Cr: 0.500 \u0026rarr; 0.09667; Cd: 0.390 \u0026rarr; 0.030). TP, Cd) in the second quarter. The RQ values for chromium and lead decreased significantly (chromium: 0.500 reduced to 0.09667; lead: 0.390 reduced to 0.03083), indicating a marked reduction in ecological risk from wastewater in the second quarter. This may be related to optimized heavy metal control processes at the cement plant. (2) NC Cement Plant: The number of moderately hazardous pollutants increased from two in the first quarter (NH₃-N, Cd) to four in the second quarter (COD, TP, Pb, Cd). The RQ value for TP rose from 0.100 to 0.58333, indicating an upward trend in ecological risk. This may be attributed to increased production loads and reduced wastewater treatment efficiency during the second quarter. (3) ZL Cement Plant: The type of high-risk pollutant (TP) remained unchanged, with TP's RQ value rising from 1.310 to 1.500. Meanwhile, the number of moderate-risk pollutants increased from 2 types (COD, Pb) in Q1 to 3 types (COD, Pb, NH3-N) in Q2, indicating a slight increase in ecological risk for wastewater during the second quarter. In summary, the wastewater discharged from these three cement plants poses varying degrees of ecological risk to the receiving water bodies. ZL Cement Plant, with its higher TP risk, is the primary high-risk source; BC Cement Plant presents a relatively moderate risk, primarily composed of heavy metals and NH₃-N; NC Cement Plant exhibits a relatively low risk. The seasonal variation in ecological risks from the wastewater of these three cement plants differs, influenced by production load adjustments and the efficiency of wastewater treatment processes. These findings provide targeted basis for developing subsequent wastewater pollution control and ecological risk management strategies for these plants, particularly prioritizing control of T at ZL Cement Plant and heavy metals at BC cement plant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary Table of Wastewater Pollutant Concentrations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOD (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBOD\u003csub\u003e5\u003c/sub\u003e (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNH4-N (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTP (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSS (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCr (VI) (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePb (mg/L)\u003c/p\u003e \u003cp\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAs (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHg (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eCd (mg/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Noise pollution risk assessment\u003c/h2\u003e \u003cp\u003eTo systematically identify the primary pollution risk sources and their spatiotemporal distribution characteristics at these three target cement plants, this section integrates non-carcinogenic health risks from air pollutants, ecological risks from wastewater pollutants, and noise disturbance risks to establish a comprehensive risk assessment framework. The comprehensive risk value for each monitoring group (BC1, BC2, NC1, NC2, ZL1, ZL2) is derived by standardizing and integrating the three risk dimensions (noise, air pollution, water pollution). Radar charts (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) visually illustrate risk variations. Comparisons and rankings based on two core dimensions\u0026mdash;spatial variations between factories and seasonal variations within factories (Q1 and Q2)\u0026mdash;aim to provide a comprehensive decision-making basis for integrated regional industrial pollution management. It should be noted that the noise risk values for all groups have been standardized to 1.000. This indicates that noise emissions from all cement plants comply with national standards (Section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e), with no risk of exceeding limits. Therefore, this value serves as the baseline reference for comprehensive risk comparison. The air pollution risk value corresponds to the HI in Section \u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e, while the water pollution risk value corresponds to the key ecological risk feature value in Section \u003cspan refid=\"Sec14\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e (derived from the RQ of primary wastewater pollutants).\u003c/p\u003e \u003cp\u003eSignificant differences in comprehensive risk levels exist among the factories, revealing a clear hierarchical distribution: ZL Cement Plant and BC Cement Plant fall into the high-risk tier, while NC Cement Plant is classified in the medium-to-low risk tier (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). ZL1 (4.175) and ZL2 (5.174) ranked second and first respectively in overall risk scores across all groups. Their notable characteristic is elevated water pollution risk, with values of 1.310 (ZL1) and 1.500 (ZL2). These figures represent 3.36 to 7.69 times higher than BC Cement Plant (0.390\u0026ndash;0.408) and 2.25 to 6.41 times higher than NC Cement Plant (0.234\u0026ndash;0.583). Although ZL Cement Plant's air pollution risk (1.865\u0026ndash;2.674) was lower than that of BC Cement Plant, the combined effect of its high -water pollution risk made it the cement plant with the highest overall risk in the second quarter.From the first quarter (4.175) to the second quarter (5.174), the total comprehensive risk increased by 23.92%. This growth was primarily driven by a 14.50% rise in air pollution risk (from 1.865 to 2.674) and a 14.50% increase in water pollution risk (from 1.310 to 1.500). Persistently high-water pollution risks coupled with escalating air pollution risks made the ZL cement plant a priority target for risk control in the second quarter.\u003c/p\u003e \u003cp\u003eIn summary, the comprehensive risks of these three cement plants exhibit distinct spatial and temporal variations: ZL Cement Plant faced the highest overall risk in the second quarter due to its elevated water pollution risk; BC Cement Plant, characterized by elevated air pollution risks, exhibited a declining trend in the second quarter; NC Cement Plant demonstrated the lowest overall risk but showed an upward trend during the second quarter. The ranking and classification of comprehensive risks provide regional environmental management authorities with a clear \u0026ldquo;target list.\u0026rdquo; Targeted control strategies should prioritize water pollution control at ZL Cement Plant and air pollution control at BC Cement Plant (Firdissa et al., 2024).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study systematically assessed the environmental risks associated with multi-media pollutants (noise, air, wastewater) from three cement plants (BC, NC, ZL) during the first and second quarters of 2024. Through single-factor and integrated risk assessments, key risk characteristics and spatio-temporal variations were identified, providing targeted support for regional pollution management. The main conclusions are as follows:\u003c/p\u003e \u003cp\u003eAll cement plants meet national standards for noise emissions (standardized risk value\u0026thinsp;=\u0026thinsp;1.000), posing no excessive risk of disturbing residents. All cement plants pose potential non-carcinogenic health risks from air pollutants (Risk Index\u0026thinsp;\u0026gt;\u0026thinsp;1). BC Cement Plant exhibits the highest air pollution risk (Risk Index: 2.730\u0026ndash;3.043), primarily from NOX, PM, and TSP, which decreased by 10.29% from Q1 to Q2. ZL (Risk Index: 1.865\u0026ndash;2.674) and NC (Risk Index: 1.671\u0026ndash;1.972) exhibit lower air pollution risks, though ZL's risk increased in the second quarter.Significant ecological risk variations exist among wastewater sources: ZL represents a high-risk source with a TP risk ratio ranging from 1.310 to 1.500; BC exhibits moderate wastewater risks (involving heavy metals and NH₃-N); NC demonstrates the lowest Q1 water quality risk, yet its Q2 risk increased by 149.15%, primarily due to elevated TP and Pb levels. Comprehensive risks exhibit distinct spatial and temporal variations: ZL showed highest risks during Q2 (severe water pollution), BC had elevated air risks with a declining trend, while NC presented the lowest overall risks but demonstrated an upward trend during Q2. Risk ranking: ZL2\u0026thinsp;\u0026gt;\u0026thinsp;BC1\u0026thinsp;\u0026gt;\u0026thinsp;ZL1\u0026thinsp;\u0026gt;\u0026thinsp;BC2\u0026thinsp;\u0026gt;\u0026thinsp;NC2\u0026thinsp;\u0026gt;\u0026thinsp;NC1. Targeted control measures should prioritize TP removal at ZL and NOx/PM reduction at BC.\u003c/p\u003e \u003cp\u003eHowever, limitations include the relatively short monitoring period and the absence of carcinogenic risk assessment. Future studies should extend the monitoring duration, incorporate carcinogenic risk analysis, and utilize numerical modeling to investigate pollutant migration patterns, thereby providing more comprehensive decision support.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCredit author statement\u003c/b\u003e \u003c/p\u003e \u003cp\u003eJie Jiang,Xin Li(First Author, these authors contributed equally to this work): Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing - Original Draft;\u003c/p\u003e \u003cp\u003eGuanhou Chen: Data Curation, Writing - Original Draft;\u003c/p\u003e \u003cp\u003eBin Li: Visualization, Investigation;\u003c/p\u003e \u003cp\u003eRong Wang: Resources, Supervision;\u003c/p\u003e \u003cp\u003eLimei Luo: Software, Validation;\u003c/p\u003e \u003cp\u003eShuai Li (Corresponding Author): Conceptualization, Funding Acquisition, Resources, Supervision, Writing - Review \u0026amp; Editing.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eDeclaration\u003c/p\u003e \u003cp\u003eThere is no funding for this article.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJie Jiang,Xin Li(First Author, these authors contributed equally to this work): Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing - Original Draft;Guanhou Chen: Data Curation, Writing - Original Draft;Bin Li: Visualization, Investigation;Rong Wang: Resources, Supervision;Limei Luo: Software, Validation;Shuai Li (Corresponding Author): Conceptualization, Funding Acquisition, Resources, Supervision, Writing - Review \u0026amp; Editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBărbulescu, A. \u0026amp; Hosen, K. 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Field monitoring data were used to evaluate single-factor risks: noise risk via national standard compliance evaluation, atmospheric non-carcinogenic risk via hazard index (HI), and wastewater ecological risk via risk quotient (RQ). Comprehensive risk integration was further performed to clarify spatiotemporal differences and identify key risk sources. Results showed that all cement plants met noise emission standards (normalized risk value\u0026thinsp;=\u0026thinsp;1.000), with no excessive nuisance risk. All plants exhibited potential atmospheric non-carcinogenic risks (HI\u0026thinsp;\u0026gt;\u0026thinsp;1), with BC cement plant having the highest air pollution risk (HI: 2.730\u0026ndash;3.043) dominated by NOₓ and particulate matter. ZL cement plant presented high wastewater ecological risk due to excessive total phosphorus (TP, RQ\u0026thinsp;=\u0026thinsp;1.310\u0026ndash;1.500). Comprehensive risk ranked as ZL2\u0026thinsp;\u0026gt;\u0026thinsp;BC1\u0026thinsp;\u0026gt;\u0026thinsp;ZL1\u0026thinsp;\u0026gt;\u0026thinsp;BC2\u0026thinsp;\u0026gt;\u0026thinsp;NC2\u0026thinsp;\u0026gt;\u0026thinsp;NC1, showing obvious seasonal variations driven by production load adjustment and pollution treatment efficiency. This study provides a standardized monitoring-assessment framework for multi-medium pollutants in cement plants, and the findings offer targeted technical support for regional industrial pollution management.\u003c/p\u003e \u003cp\u003e \u003cdiv description=\"\" class=\"Drawing\" id=\"211718783\" name=\"图片 7\"\u003e\u003c/div\u003e \u003c/p\u003e","manuscriptTitle":"Monitoring-Based Comprehensive Environmental Risk Assessment of Multi-Medium Pollutants and Spatiotemporal Differences in Three Typical Cement Plants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-31 13:17:37","doi":"10.21203/rs.3.rs-8838504/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"80995425966820171693419647521459595166","date":"2026-04-25T22:52:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-27T11:45:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T10:40:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T10:40:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2026-02-10T08:07:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6565a489-00bb-4bff-a146-afe1e5abbead","owner":[],"postedDate":"March 31st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-31T13:17:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-31 13:17:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8838504","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8838504","identity":"rs-8838504","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}