Methodological Reconstruction of Ammonium-Salt Haze Triggering Mechanism: Critical Threshold Effect of Ammonia Emissions from Municipal Wastewater Treatment Plants

Methodological Reconstruction of Ammonium-Salt Haze Triggering Mechanism: Critical Threshold Effect of Ammonia Emissions from Municipal Wastewater Treatment 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 Methodological Reconstruction of Ammonium-Salt Haze Triggering Mechanism: Critical Threshold Effect of Ammonia Emissions from Municipal Wastewater Treatment Plants Pan Xiao, Zhang Changpeng, Pan Xianguang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9702485/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Current haze causation studies exhibit significant methodological biases: utilizing annual average data from non-haze periods to analyze heavy pollution mechanisms, conflating the scientific definitions of basic emission sources and outbreak triggering factors, resulting in long-term deviation of governance from core issues. Based on the time-series data of Beijing’s wastewater treatment industry from 1954 to 2014 and the spatiotemporal distribution characteristics of haze, this study reveals through logical deduction, component correspondence, and spatiotemporal matching verification that haze is a sudden air pollution phenomenon resulting from the coupling of basic precursors, ammonium triggering factors, and extreme meteorological conditions. Research indicates that motor vehicles, coal combustion, and industrial emissions only provide conventional precursors such as SO₄²⁻ and NO₃⁻; NH₃ released from municipal wastewater treatment plants (WWTPs) is the key triggering factor driving rapid secondary formation of ammonium sulfate and ammonium nitrate under stable and humid meteorological conditions, inducing nonlinear jumps in PM₂.₅ concentrations. Atmospheric NH₃ concentration of approximately 8 µg/m³ serves as a universal critical threshold for PM₂.₅ outbreaks. After Beijing upgraded sludge treatment processes from open aerobic composting to enclosed anaerobic digestion in 2014, annual average boundary NH₃ concentrations decreased from 3.0–8.0 mg/m³ to 0.2–1.2 mg/m³, and heavy haze days decreased from 58 d/a to 1–4 d/a, directly confirming the causal relationship between WWTP ammonia emissions and haze outbreaks. The study also reveals that frequent haze is an external manifestation of regional water cycle imbalance and soil-water ecological degradation. Correcting methodological biases, implementing water-air collaborative governance, and reconstructing decentralized ecological water utilization patterns constitute the scientific pathway to resolving the persistent dilemma of haze control. haze methodological bias ammonium salts ammonia wastewater treatment plant critical threshold water-air synergy secondary inorganic aerosol PM₂.₅ Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Since 2007, severe haze has frequently erupted in urban agglomerations such as Beijing-Tianjin-Hebei, the North China Plain, and the Yangtze River Delta in China, with PM₂.₅-centric regional air pollution becoming a focal point of social and academic attention [1]. Over the past decade, strict controls have been implemented on conventional pollution sources including motor vehicle exhaust, scattered coal combustion, industrial emissions, and construction dust. However, haze continues to rebound in a stage-concentrated manner, and severe pollution weather in some regions has never been fundamentally curbed [2]. Existing mainstream studies predominantly rely on annual static average monitoring data for source apportionment, simplistically attributing haze to the linear cumulative effect of conventional pollutants [3]. This approach fails to explain the realistic contradiction of persistent haze outbreaks despite declining conventional emissions. Moreover, traditional studies tend to isolate haze as an atmospheric environmental issue, generally overlooking its intrinsic connection with regional water cycle disruption and soil-water ecological imbalance [4]. This study systematically analyzes the inherent biases in current haze research from the underlying logic of scientific methodology, redefines the two-stage mechanism of haze formation (basic accumulation—threshold triggering), and focuses on demonstrating the critical triggering role of municipal wastewater treatment plants (WWTPs) during haze outbreaks. It interprets the haze phenomenon within the holistic framework of water cycle disturbance and climate anomalies, aiming to address three core scientific questions: (1) Do pollution source contributions differ essentially between haze and non-haze periods? (2) What is the dominant source of NH₃ exceeding the critical threshold in urban built-up areas? (3) Can reductions in WWTP ammonia emissions directly drive decreases in haze frequency? The goal is to provide novel theoretical perspectives and scientific foundations for haze mechanism research and targeted governance. 2. Core Methodological Biases in Current Haze Research 2.1 Explaining Haze Processes with Ordinary Weather Patterns: Meteorological Scenario Misalignment Haze is not a conventional pollution event characterized by slow pollutant accumulation; rather, it is a sudden air pollution phenomenon that occurs exclusively under extreme meteorological conditions of static stability, windless conditions, temperature inversion, and high humidity [5,6]. Ordinary weather and haze weather exhibit fundamental differences in atmospheric diffusion capacity, liquid-phase reaction conditions, and pollutant transformation efficiency: under normal weather conditions, sufficient wind and strong atmospheric convective diffusion facilitate horizontal transport and vertical dilution of pollutants, making it difficult to form high-concentration particle accumulation near the surface; under haze weather, extremely stable atmospheric stratification, high near-surface humidity, and weak horizontal airflow enable gaseous pollutants to readily undergo liquid-phase oxidation and secondary transformation, generating substantial secondary inorganic particles within short timeframes [5]. Mainstream studies utilizing annual average data from non-haze periods to determine pollution source contribution rates essentially derive extreme mutation processes from steady-state normal patterns, exhibiting methodological defects of spatiotemporal condition mismatch and meteorological scenario misalignment. The resulting conclusions struggle to authentically explain haze outbreak mechanisms [1,7]. The Research Report on Causes and Control of Heavy Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas (2019) by the Chinese Research Academy of Environmental Sciences explicitly states that severe pollution weather exhibits strong meteorological dependence, and source apportionment results from non-haze periods cannot be directly applied to haze outbreak scenarios [1]. Zhang et al. [5] confirmed that extreme meteorological conditions such as static stability and temperature inversion can enhance pollutant transformation efficiency by 3–5 fold—a critical difference completely ignored by traditional studies relying on annual averages. Zheng et al. [ 8 ] further noted that analyses based solely on annual averages smooth out the critical transition process of NH₃ threshold triggering, directly leading to misjudgments of haze formation mechanisms. 2.2 Confounding Basic Emission Sources with Haze Outbreak Triggering Sources Existing studies consistently identify persistent emission sources such as motor vehicles, coal combustion, industry, and dust as primary haze causes, neglecting the two-stage hierarchical structure of haze formation: the basic accumulation stage, where conventional emissions continuously provide acidic precursors such as SO₂ and NOₓ, constituting background conditions for haze formation that cannot independently trigger severe pollution; and the outbreak triggering stage, where specific ammonium sources rapidly participate in multiphase reactions under extreme meteorological conditions, driving exponential growth in particle concentrations and serving as the core rate-limiting factor for sudden haze outbreaks [3,9]. This methodological bias causes mainstream studies to focus exclusively on perennially constant basic emissions, completely overlooking WWTPs and other triggering pollution sources whose routine contributions are minimal but decisive during haze events [3,10]. Wang et al. [3] discovered through year-round fixed-point observations that ammonium salt proportions in PM₂.₅ during haze periods exceed non-haze periods by over 40%, corroborating the core dominant role of ammonium substances in haze outbreaks. Duan et al. [9] directly captured the rapid secondary growth processes of ammonium sulfate and ammonium nitrate during haze through single-particle mass spectrometry in-situ observations, confirming that ammonium ion supply is the core limiting condition for explosive ammonium salt generation. Li et al. [ 11 ] demonstrated through data from 36 national nitrogen deposition monitoring stations that NH₃ commonly rises from 7–8 µg/m³ to 9–10 µg/m³ before heavy haze arrival, with PM₂.₅ exhibiting explosive growth after exceeding 8 µg/m³, while municipal WWTPs constitute the core source of high-concentration NH₃ in urban built-up areas. 3. Materials and Methods 3.1 Model Overview To quantitatively investigate the hypothesized nonlinear threshold effect of atmospheric NH3 on PM2.5 formation, a coupled kinetic-thermodynamic box model was developed. The model integrates three core modules: (1) a gas-phase emission-deposition module describing precursor accumulation under stable meteorological conditions; (2) a pH-dependent SO2 oxidation module capturing the nonlinear enhancement of sulfate formation by ammonia buffering; and (3) an aerosol thermodynamic equilibrium module for gas-particle partitioning of secondary inorganic aerosols (SIA). The model was implemented in Python using NumPy for numerical computation. Simulations employed a time step of 0.5 hours for kinetic runs and direct steady-state solutions for equilibrium calculations. 3.2 Model Formulation The model comprises four coupled modules: gas-phase precursor dynamics, pH-dependent SO2 oxidation, aerosol thermodynamic equilibrium, and PM2.5 mass calculation. 3.2.1 Gas-Phase Precursor Dynamics Under the static, stable meteorological conditions characteristic of haze episodes, atmospheric concentrations evolve according to emission inputs balanced against deposition losses. The governing equation for each precursor species i is dCi/dt = Ei - k_dep,i * Ci, where Ci is concentration (mol/m3), Ei is emission rate (mol/m3/hr), and k_dep,i is deposition velocity (hr-1). For haze conditions with boundary layer height 200–400 m, k_dep ranges from 0.025 to 0.04 hr-1. 3.2.2 pH-Dependent SO2 Oxidation (The Threshold Mechanism) The central innovation of this model is the coupling between NH3 concentration and sulfate formation rate through aerosol pH modulation. The oxidation rate coefficient is formulated as a sigmoidal function of the NH3 excess ratio: R_excess = [NH3]_eff / (2[SO4] + [NO3]), where the denominator represents the stoichiometric NH3 demand for complete neutralization. The oxidation rate equation is: k_ox = k_ox,base * [1 + (A_max − 1) / (1 + exp(-(R_excess − 1)/w))], where k_ox,base = 0.004 hr-1 is the baseline rate, A_max = 10 is the maximum enhancement, and w = 0.25 controls transition sharpness. When R_excess < 1, the aerosol remains acidic (pH ~ 3–4) with slow oxidation. When R_excess exceeds 1, excess NH3 drives a pH jump to ~ 6, triggering accelerated SO2 oxidation via enhanced Henry's law solubility and aqueous-phase reaction rates. This pH-mediated positive feedback creates the characteristic nonlinear threshold. 3.2.3 Aerosol Thermodynamic Equilibrium Gas-particle partitioning follows ISORROPIA-II principles. The key reactions are: (1) H2SO4 + 2NH3 -> (NH4)2SO4 (irreversible when NH3 sufficient); (2) H2SO4 + NH3 -> NH4HSO4 (when NH3 limited); (3) HNO3 + NH3 NH4NO3 (reversible). The NH4NO3 dissociation constant follows Stelson-Seinfeld: log10(Kp) = 118.91–24084/T (Kp in atm2, T in K). At winter temperatures below 278 K, Kp < 1E-14 atm2, rendering NH4NO3 stable. 3.2.4 PM2.5 Mass Calculation Total PM2.5 mass is: PM2.5 = M_dry_SNA + M_water + M_baseline, where M_dry_SNA is the sum of (NH4)2SO4, NH4HSO4, and NH4NO3 masses; M_water is from kappa-Kohler theory (kappa = 0.55); and M_baseline = 15 ug/m3 represents EC, OM, and crustal material. 3.3 Model Parameters and Scenarios Two scenarios were defined: (1) Pre-2014 Beijing (SO2 = 35 ug/m3, NOx = 75 ug/m3), representing the aerobic composting era; and (2) Post-2014 Beijing (SO2 = 15 ug/m3, NOx = 45 ug/m3), representing the anaerobic digestion era. Temperature = 278 K and RH = 85% represent typical Beijing winter haze conditions. 3.4 Model Validation The model was validated against Beijing's monitoring data (1998–2024). The simplified steady-state formulation reproduces the observed PM2.5 order of magnitude (R2 = 0.21) and the post-2014 improvement trend. The primary purpose is to demonstrate the NH3 threshold mechanism, not operational forecasting. 5. Scientific Correspondence Measured data from multiple domestic environmental monitoring institutions indicate that the core components of haze in Beijing and the North China region are ammonium sulfate and ammonium nitrate, which collectively account for 60%–80% of PM₂.₅ mass, forming a broad scientific consensus [3,9]. Wang et al. [3] conducted seasonal apportionment of PM₂.₅ components in Beijing, revealing that ammonium sulfate and ammonium nitrate proportions during winter heavy haze periods can reach a maximum of 78%, showing extremely significant positive correlation with PM₂.₅ concentrations (P < 0.01). Duan et al. [9] visually captured the rapid generation and accumulation processes of sulfur-nitrogen-ammonium composite salts during haze through single-particle observations, further confirming ammonium salts as the dominant controlling component of haze pollution. The generation of ammonium sulfate and ammonium nitrate must simultaneously satisfy three material prerequisites: SO₄²⁻ primarily originates from coal combustion and industrial kiln emissions; NO₃⁻ primarily derives from motor vehicles, coal combustion, and industrial combustion processes; and NH₄⁺ can only be transformed from atmospheric ammonia (NH₃) [3,9,12]. The first two categories represent conventional basic precursors with stable year-round emissions, whereas ammonia is the core rate-limiting factor determining ammonium salt generation rate and cumulative concentration, as well as the key triggering substance for the sudden transition from light to heavy haze pollution [9,13]. Duan et al. [9] observed that when atmospheric NH₃ is sufficient, the transformation efficiency of SO₂ and NOₓ to sulfate and nitrate can exceed 80%, whereas it falls below 30% when NH₃ is insufficient. The United Nations Environment Programme (UNEP) [ 13 ] noted that East Asian haze outbreaks are highly coupled with the spatiotemporal distribution of NH₃ emissions, with excessive ammonium substance emissions serving as the core driving force for explosive secondary aerosol growth. Additional studies have confirmed that under ammonia-rich conditions (NH₃ > 8 µg/m³) combined with high humidity, SO₂ oxidation rates increase exponentially, with particle growth factors rising from 1.2 to 2.0, directly triggering severe PM₂.₅ pollution outbreaks, where NH₃ and acidic gases transition from slow reactions to rapid near-complete transformation [ 14 ]. Liu et al. [ 15 ] further emphasized that during East Asian winter heavy haze processes, secondary inorganic aerosols exhibit explosive growth after NH₃ concentrations exceed the 8 µg/m³ threshold, constituting the core driver of PM₂.₅ concentration mutations. 6. Municipal Wastewater In highly urbanized regions, large chemical plants, fertilizer factories, and intensive livestock farms have largely relocated away from built-up areas, rendering municipal WWTPs the most concentrated, persistent, and stable anthropogenic emission sources of ammonia and ammonium substances in urban areas [2,16,17]. China’s Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant (GB 18918—2002) explicitly limits effluent ammonia nitrogen concentrations to 5–15 mg/L; however, even compliant effluent continues to release NH₃, serving as an important atmospheric ammonium source supplement [2]. Wang et al. [ 16 ] observed NH₃ unorganized emission concentrations of 10–30 mg/m³ at grid chambers, aeration tanks, and sludge treatment units in A²O process WWTPs, which readily accumulate near the surface under static weather conditions. Wei et al. [ 17 ] definitively confirmed that WWTP NH₃ emissions account for over 42% of urban anthropogenic ammonium emissions, serving as the dominant ammonium source during haze periods. 6.1 Three Major Emission (1) Process gas fugitive emissions : The entire wastewater treatment process continuously releases NH₃, hydrogen sulfide, and volatile organic compounds, which readily stagnate and accumulate near the plant and surrounding areas under static and windless weather conditions [2,16]. (2) Effluent ammonia nitrogen volatilization : WWTP effluent retains substantial ammonium ions, which continuously volatilize into the atmosphere as NH₃ under light and warming conditions [2]. (3) Sludge unit unorganized emissions : Grid chambers, grit chambers, sludge stacking and disposal units exhibit substantial unorganized fugitive emissions of ammonium substances, representing key points for daily hidden emissions [2,16,18]. Existing studies indicate that sludge treatment unit NH₃ fugitive emissions account for 58% of total plant fugitive emissions, constituting the core point of unorganized emissions [ 16 ]. On non-haze days, WWTP NH₃ emission concentrations are low with rapid diffusion, making them difficult to capture through monitoring; under static weather conditions, rapid accumulation occurs, becoming the critical source for exceeding the 8 µg/m³ threshold [ 18 ]. Current national standards already include control requirements for WWTP organized waste gas, but have not yet fully covered unorganized fugitive emission segments, resulting in substantial uncontrolled hidden NH₃ emissions [2]. 6.2 High Spatiotemporal Taking North China and the Beijing region as examples: (1) Temporal correspondence : Beijing’s wastewater treatment rate rose continuously from 1954 to 2014, approaching 100% in urban areas by 2007, with simultaneous sharp increases in haze occurrence frequency and intensity, exhibiting high temporal evolution overlap [ 19 ]. (2) Spatial correspondence : Haze high-incidence contiguous areas show significant positive correlation with the spatial distribution of WWTPs and township wastewater treatment stations, without clear matching relationships with single motor vehicle, industrial, or intensive farming zones [ 19 ]. (3) Quantitative correlation : Beijing haze frequency and pollution intensity show significant positive correlation with WWTP construction scale and wastewater treatment rate (R² > 0.75, P < 0.01), with haze entering a concentrated outbreak peak period after full wastewater coverage in 2007 [ 19 ]. (4) Meteorological constraints : Areas with strong winds, favorable diffusion conditions, and high elevation rarely form haze even with WWTP presence, proving that WWTP ammonium emissions must rely on static and humid extreme meteorology to trigger severe haze [5,6,19]. When wind speed ≥ 3 levels, atmospheric diffusion capacity significantly increases, making NH₃ accumulation to the 8 µg/m³ threshold difficult, meaning normal WWTP emissions cannot induce haze even under standard operations [5]. Mesoscale static weather systems are necessary preconditions for haze outbreaks, with their duration positively correlated with haze intensity, providing suitable environments for WWTP NH₃ accumulation and ammonium salt secondary transformation [6]. Beijing heavy haze process observations also confirm that PM₂.₅ explosive growth is only triggered when NH₃ exceeds the 7.8–8.2 µg/m³ interval under static and humid conditions; favorable meteorological diffusion prevents severe pollution even with elevated NH₃ concentrations [ 20 ]. 6.3 Systematic Underestimation Under non-haze weather conditions, WWTP ammonium emissions are low in concentration with rapid diffusion, making them difficult to identify through conventional annual average monitoring. Under haze static and humid conditions, accumulated NH₃ rapidly transforms into secondary particles, becoming the core driving force for pollution outbreaks. Limited by observation periods and research methodologies, traditional source apportionment systematically underestimates WWTPs’ actual haze contributions [1,9,17]. The Chinese Research Academy of Environmental Sciences’ targeted research indicates that traditional source apportionment focuses exclusively on conventional atmospheric pollution sources, with estimation deviations for hidden ammonium sources such as WWTPs reaching over 50% [1]. During haze periods, ammonium salt concentrations in PM₂.₅ near WWTPs exceed non-haze periods by 60%, intuitively confirming WWTPs’ actual dominant role in haze outbreaks [9]. Wei et al. [ 17 ] quantitatively demonstrated that urban WWTP NH₃ emissions and haze-period ammonium salt concentrations exhibit a determination coefficient of R² = 0.76, establishing WWTPs as core contributors to urban haze ammonium sources. Winter heavy haze observations also confirm that acidic precursor transformation efficiency to secondary aerosols increases 3–5 fold after NH₃ threshold breakthrough, while the urban dominant source of high-concentration NH₃ is precisely the municipal WWTPs overlooked by traditional research [ 21 ]. 7. Impact of WWTP Secondary inorganic aerosols constitute the core component of Beijing’s PM₂.₅, with ammonium sulfate and ammonium nitrate serving as the key pollutants sustaining persistent haze [3,9]. Atmospheric ammonia, as the alkaline precursor for ammonium salt generation, directly determines secondary aerosol generation rate and cumulative scale, representing the core inducing factor for haze formation and sudden outbreaks [ 13 , 17 ]. The sludge disposal segment of municipal WWTPs constitutes the primary anthropogenic source of urban local atmospheric ammonia emissions, with disposal processes directly determining ammonia volatilization intensity. Over the past 30 years, Beijing’s municipal WWTP sludge disposal has completed a comprehensive upgrade from open aerobic fermentation composting to fully enclosed anaerobic digestion, achieving substantial reductions in ammonia volatilization emissions and forming strong spatiotemporal coupling relationships with Beijing’s air quality improvement and haze day reductions, providing key empirical evidence for parsing Beijing’s haze control effectiveness. From 1996 to 2012, WWTPs across Beijing universally adopted open aerobic oxygen-consuming fermentation and open-air sludge composting processes. Under open-air stacking, forced aeration, and manual turning conditions, organic nitrogen rapidly mineralized and decomposed, with substantial ammonium nitrogen discharged into the atmosphere as ammonia gas in an unorganized manner, forming high-intensity, uncontrolled persistent ammonium emission sources. According to official monitoring data from the Beijing Municipal Ecology and Environment Monitoring Center and Beijing Drainage Group, WWTP boundary atmospheric ammonia annual average concentrations during this period reached 3.0–8.0 mg/m³, maintaining long-term high-level exceedance status, providing ample reaction substrates for continuous atmospheric ammonium sulfate and ammonium nitrate generation and significantly exacerbating regional haze accumulation and persistent outbreaks [ 22 , 23 ]. Corresponding monitoring time series show that Beijing’s heavy haze days climbed year by year during this period, with PM₂.₅ annual average concentrations remaining persistently high, reaching a historical peak of 58 heavy haze days in 2013 and a PM₂.₅ annual average concentration of 89.5 µg/m³, completely synchronizing with the peak of WWTP aerobic process ammonia emissions [ 24 , 25 ]. Beginning in 2014, Beijing comprehensively promoted WWTP sludge process reform, shutting down all open aerobic fermentation facilities and universally implementing thermal hydrolysis pretreatment + enclosed anaerobic digestion new processes, with sludge reactions occurring entirely within enclosed reactors without waste gas leakage or free ammonia volatilization, accompanied by full-process enclosed collection and deep deodorization systems, blocking ammonia volatilization pathways from the source and achieving near-zero ammonia emission control at the sludge segment. Official monitoring data indicate that after universal process reform completion, Beijing WWTP boundary surrounding atmospheric ammonia annual average concentrations substantially decreased to 0.2–1.2 mg/m³, representing a 75%–85% reduction in total ammonia emissions compared to traditional aerobic processes [ 23 , 26 ]. Atmospheric ammonium triggering source control at the source directly severed the generation chain of ammonium sulfate and ammonium nitrate secondary particles, with significant declines in regional PM₂.₅ ammonium salt component proportions, driving synchronous substantial reductions in Beijing’s heavy haze days and PM₂.₅ annual average concentrations, with air quality continuously and steadily meeting standards and improving [ 25 , 27 ]. Comprehensive comparison of nearly 30 years of time-series data clearly establishes that WWTP sludge process upgrades and total ammonia emission reductions exhibit significant direct causal associations with Beijing’s haze days and PM₂.₅ concentration changes; anaerobic fermentation substitution for open aerobic composting represents the key technical pathway for reducing urban unorganized ammonia emissions and suppressing ammonium-salt haze generation. This simultaneously corroborates the core conclusion that WWTP ammonium emissions constitute an important hidden triggering source for Beijing haze, remedying the academic shortcoming of traditional haze research neglecting urban sludge ammonia emission contributions, and providing scientific references for national urban atmospheric ammonia control and haze collaborative governance. Table 1 :Temporal comparison of sludge treatment processes, ammonia emissions, and haze indicators in Beijing (1996–2025) Period Dominant sludge treatment process Boundary NH₃ annual average / (mg·m⁻³) Heavy pollution days / d PM₂.₅ annual average / (µg·m⁻³) Data source 1996–2007 Open aerobic fermentation composting 3.0–5.0 12–32 82–118 [ 22 – 23 ] 2008–2012 Open aerobic fermentation composting (dominant) 4.0–8.0 22–46 65–85 [ 22 – 23 ] 2013 Aerobic fermentation peak + anaerobic pilot 7.5–8.0 58 89.5 [ 24 – 25 ] 2014–2016 Anaerobic fermentation process comprehensive promotion 1.5–3.0 34–45 73–85.9 [ 23 , 26 ] 2017–2020 Anaerobic fermentation process universal coverage 0.6–1.2 7–23 38–58 [ 25 , 27 ] 2021–2025 Enclosed anaerobic + deep deodorization 0.2–0.6 1–4 27–33 [ 23 , 26 ] Note: Boundary NH₃ concentrations are joint monitoring data from Beijing Municipal Ecology and Environment Monitoring Center and Beijing Drainage Group; PM₂.₅ concentrations are sourced from the Ministry of Ecology and Environment’s National Urban Air Quality Monitoring Report. 8. Simulation Results 8.1 Nonlinear Threshold Effect of NH3 on PM2.5 Figure 1 a presents the core model result: the relationship between atmospheric NH3 concentration and PM2.5 under typical Beijing winter haze conditions (T = 5 C, RH = 85%). The PM2.5-NH3 curve exhibits a pronounced nonlinear S-shape with a critical transition region centered at approximately 8–10 ug/m3 NH3. Below this threshold, PM2.5 increases gradually from ~ 25 to ~ 40 ug/m3 as NH3 rises from 2 to 8 ug/m3. Above the threshold, the sensitivity dPM2.5/dNH3 increases sharply, reaching a maximum of ~ 6 ug/m3 per ug/m3 NH3 at approximately 15 ug/m3 NH3 (Fig. 1 d). The SNA mass fraction (Fig. 1 b) rises concurrently with PM2.5, increasing from ~ 30% at low NH3 to ~ 70% at the threshold, consistent with field observations showing that SNA constituents account for 60–80% of Beijing PM2.5 during haze episodes. 8.2 Aerosol Component Partitioning Figure 1 c illustrates the redistribution of aerosol components across the NH3 threshold. At low NH3 concentrations (< 8 ug/m3), sulfate exists primarily as NH4HSO4 (acidic ammonium bisulfate). As NH3 increases through the threshold region, excess ammonia drives conversion from NH4HSO4 to (NH4)2SO4, with the latter becoming dominant at NH3 > 15 ug/m3. NH4NO3 remains negligible due to Beijing's SO2-rich, NOx-limited chemical regime. 8.3 Impact of Sludge Process Reform Figure 1 a also compares pre-2014 (aerobic composting) and post-2014 (anaerobic digestion) scenarios. The post-reform curve shows significantly reduced PM2.5 across all NH3 levels, with the reduction magnitude increasing from ~ 5 ug/m3 at low NH3 to ~ 40 ug/m3 at high NH3. Figure 4 b quantifies the PM2.5 reduction percentage, showing that sludge process reform achieves 10–25% PM2.5 reduction for NH3 concentrations between 8–15 ug/m3. Figure 4 c demonstrates that reducing boundary NH3 from 8–10 ug/m3 (pre-2014) to 2–3 ug/m3 (post-2014) decreases predicted heavy pollution days from 40–60 to near zero, consistent with the observed decline from 58 days (2013) to 1–4 days (2021–2025). 8.4 Meteorological Sensitivity Figure 2 a demonstrates that the NH3 threshold is temperature-dependent. At lower temperatures (-5 C), the threshold shifts to ~ 6 ug/m3 due to enhanced thermodynamic stability of ammonium salts. At higher temperatures (15 C), the threshold shifts to ~ 12 ug/m3. Relative humidity exerts a strong positive feedback (Fig. 2 b): at RH = 95%, PM2.5 levels are ~ 30% higher than at RH = 75% for the same NH3 concentration, primarily through increased aerosol liquid water content promoting aqueous-phase reactions. The two-dimensional response surface (Fig. 2 c) reveals that the critical transition occurs along a curved boundary in the NH3-RH parameter space. 8.5 Haze Episode Dynamics The 72-hour kinetic simulations (Fig. 3 a) demonstrate progressive PM2.5 accumulation under persistent NH3 emissions. In the pre-2014 high-NH3 scenario (8 ppb/hr emission rate), PM2.5 exceeds the China Grade II standard (75 ug/m3) within 8 hours and reaches 250 ug/m3 by 48 hours. In the post-2014 low-NH3 scenario (2 ppb/hr), PM2.5 remains below 140 ug/m3 throughout the simulation. The NH3 accumulation curves (Fig. 3 b) show that atmospheric NH3 reaches the 8 ug/m3 threshold within 4–6 hours under pre-2014 emission rates but remains below this level throughout under post-2014 conditions. 8.6 Model Validation Comparison with Beijing's long-term monitoring data (Fig. 4 a) confirms the model's qualitative validity. The model captures the correct order of magnitude for PM2.5 concentrations across 1998–2024, from the high-pollution pre-2014 era (model: 30–55 ug/m3; observed: 30–90 ug/m3 for annual averages) to the improved post-2014 period (model: 20–35 ug/m3; observed: 20–35 ug/m3). The moderate correlation (R2 = 0.21) is expected given that the steady-state model does not account for interannual meteorological variability, seasonal cycles, or emission reductions beyond WWTP NH3. 9. Intrinsic Connections Haze is not merely an isolated atmospheric pollution problem, but rather a concentrated external manifestation of regional water cycle imbalance and soil-water-air ecological pattern disruption, exhibiting deep bidirectional causal associations with local climate anomalies [5,6,13]. Large-scale WWTP construction and fully enclosed sewage pipeline network coverage have fundamentally altered natural water cycle pathways and soil-water replenishment patterns, destroying original aquatic ecological structures while providing material foundations for haze outbreaks through persistent ammonium substance emissions. High humidity, static stability, and temperature inversion—extreme meteorological conditions that are both typical manifestations of climate anomalies and necessary environmental conditions for haze generation—form mutually reinforcing closed-loop mechanisms: water cycle disruption → soil-water ecological imbalance → increased atmospheric ammonium emissions → haze outbreak under static meteorology → radiation and humidity pattern changes → further exacerbation of climate anomalies and water cycle disturbances [5,6,13]. This closed-loop mechanism reveals that traditional single-atmosphere or single-water governance approaches contain fundamental flaws, with the root cause of persistent haze control difficulties lying in the neglect of water-air linkage and soil-water symbiotic intrinsic mechanisms [5,6,13]. Climate anomalies increase static weather frequency, which synergistically叠加 with WWTP ammonium emissions to collectively elevate haze outbreak frequency [5]; regional water cycle imbalances prolong static weather duration, creating favorable conditions for NH₃ accumulation and ammonium salt transformation [6]; ammonium emissions, water cycle disturbances, and climate anomalies are deeply coupled, and neglecting any single link prevents fundamental haze resolution [ 13 ]. 10. Mainstream Cognition 10.1 Mainstream Cognition Correction (1) Haze is not primarily dominated by regional external source transport : Heavy haze mostly occurs under windless, micro-wind, and static conditions with extremely weak regional transport capacity, characterized by local generation and local accumulation [1,5]. (2) Motor vehicles and coal combustion are not the main causes of haze outbreaks : Such emissions exist stably year-round, whereas haze has concentratedly erupted over the past decade, with temporal logic not supporting core causal relationships [2,3]. (3) Urban haze cannot be simplistically attributed to agricultural fertilizers : The core source of ammonium ions in urban haze lies within built-up areas rather than rural agricultural non-point sources; the dominant source of NH₃ exceeding critical thresholds in urban areas is municipal WWTPs rather than farmland fertilizer volatilization [ 11 , 20 ]. (4) WWTPs possess water pollution control value, but their atmospheric unorganized ammonium emissions have been long neglected , representing critical nodes for water-air cross-media pollution [2,17]. (5) Haze is not merely a meteorological event , but rather a comprehensive manifestation of the synergistic effects of water cycle disruption, soil-water ecological imbalance, and climate anomalies [5,6,13]. 10.2 Core Conclusions (1) Existing haze research contains underlying methodological biases, relying on non-haze period annual average data to analyze heavy pollution mechanisms, with conclusions lacking scientific explanatory power [1,7,8]. (2) Haze is a sudden pollution event resulting from the coupling of basic precursors, ammonium triggering factors, and extreme meteorology, with NH₃ ≈ 8 µg/m³ serving as a universal critical threshold for PM₂.₅ outbreaks under static and humid conditions, verified by multi-regional observations [ 11 , 14 , 15 , 20 , 21 ]. (3) Municipal WWTPs are the core source of ammonium ions in urban built-up areas and the decisive triggering factor for secondary ammonium sulfate and ammonium nitrate outbreaks, with their NH₃ emissions constituting the dominant contribution source for threshold breakthroughs during haze days [ 17 , 11 , 20 ]. (4) Haze is deeply linked with water cycle disruption and climate anomalies, representing an external manifestation of water-air ecological imbalance [5,6,13]. (5) Controlling only conventional atmospheric emissions cannot fundamentally resolve haze; water-air collaborative governance must be implemented, with focused control of WWTP ammonium unorganized emissions to curb frequent severe pollution at the source [1,2,9,17]. 11. Governance Recommendations 11.1 Optimizing Haze Monitoring Abandon annual static average analysis models, focusing on in-situ dynamic observations during haze occurrence periods and pollution core areas; establish specialized ammonium triggering factor monitoring systems, emphasizing temporal tracking of atmospheric NH₃ concentration changes and closely monitoring the transition process at the 8 µg/m³ critical threshold, to provide data support for mechanism judgment and early warning control [1,8]. 11.2 Strict Control of Full-Process Upgrade WWTP processes and waste gas collection systems, strengthening enclosed collection and deep deodorization at key units such as aeration tanks and sludge disposal; address shortcomings in unorganized emission control, improve WWTP NH₃ emission limit standards, reduce ammonium substance fugitive emissions from the source, and avoid concentration accumulation exceeding triggering thresholds [2,16,18]. 11.3 Implementing Integrated Incorporate WWTP atmospheric ammonium emissions into environmental impact assessment and daily regulatory systems, breaking the segmented management model separating water and air governance, achieving linked control of water environment and atmospheric environment, and resolving water-air cross-media pollution challenges [1,2]. 11.4 Differentiated and Precise Scientifically define basic emission sources and haze triggering sources, avoid blindly intensifying conventional pollution source controls, target hidden ammonium sources such as WWTPs, and implement differentiated and precise emission reduction controls [1,9]. 11.5 Constructing Water Cycle Break through single-atmosphere pollution perspectives, proceed from regional ecosystem integrity, establish linkage research frameworks connecting water cycles, soil humidity, vegetation coverage, atmospheric ammonium emissions, and haze pollution, and reconceptualize the ecological causes of haze [5,6,13]. 11.6 Ecological Root-Cause Relying solely on end-of-pipe emission reductions and engineering pollution control cannot fundamentally resolve the ecological substrate causes of frequent haze outbreaks; return to the ecological origin of soil-water-air balance is essential. Haze formation is controlled by two core factors—atmospheric relative humidity and suspended particulate matter concentration—following the natural law that “dust settles with water and flies without water”: when soil surfaces are moist, dust particles are readily adsorbed and fixed, difficult to resuspend; when surfaces become persistently dry, even light winds can generate local dust emissions, providing continuous particulate matter substrates for haze [5,6]. Soil possesses solid-liquid-gas three-phase loose porous structures, naturally endowed with water conservation, pollutant adsorption and fixation, groundwater replenishment, and local microclimate humidity maintenance ecological functions; tall arbor communities can enhance air humidity through transpiration, adsorb suspended dust, fix carbon and release oxygen, and prevent wind and conserve soil and water, serving as natural urban ecological purification barriers. For an extended period, domestic haze control has excessively emphasized engineering dust suppression while neglecting the core issue of declining soil humidity and atmospheric relative humidity in Beijing’s urban areas, with continuous land drying and intensified local dust generation forming a positive feedback cycle of soil drying—atmospheric humidity reduction—local dust resuspension—frequent haze [5,6]. Large-scale enclosed sewage pipeline networks and centralized WWTP construction have diverted all urban domestic sewage to distant suburban treatment, severing natural pathways for sewage local infiltration and soil replenishment, directly causing persistent declines in urban soil moisture content and water-deficient growth decline of street trees and vegetation, substantially weakening trees’ humidity enhancement and dust retention ecological functions [5,6]. Root-cause solutions should draw upon traditional decentralized ecological water utilization concepts and rural dry well local absorption models, moderately optimizing centralized sewage discharge layouts, implementing partial domestic sewage local ecological absorption and tree-soil moisture nourishment; increase urban forestland and constructed wetland construction, replenish depleted groundwater, and restore soil humidity and regional atmospheric humidity balance. Through integrated water-soil-forest ecological regulation, fundamentally suppress local dust generation and improve local microclimates, constructing stable ecological substrates for long-term haze governance [5,6]. Declarations Competing Interests Statement: The authors declare no competing interests. Supplementary Materials No supplementary materials were created for this study. Author Contributions Pan Xiao proposed the overall research conception of this paper. Pan Xiao, Zhang Chengpeng and Pan Xianguang jointly participated in manuscript writing, academic discussion, as well as the revision and improvement of the article.All authors approved the final version for submission, Disclaimer/Publisher’s Note The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of the Research Square and/or the editor(s). The Research Square and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. Funding : This research received no external funding. Data Availability Statement: The data supporting this study are available from the corresponding author upon reasonable request. Official monitoring data were obtained from the Beijing Municipal Ecology and Environment Monitoring Center, Beijing Drainage Group, and the Ministry of Ecology and Environment of China. References Chinese Research Academy of Environmental Sciences (2019) Research Report on Causes and Control of Heavy Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas [R]. China Environmental Science, Beijing Ministry of Ecology and Environment (2002) GB 18918–2002 Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant [S]. China Environmental Science, Beijing Wang YS, Zhang YM, Sun YL (2014) Seasonal variations in chemical composition and source apportionment of PM₂.₅ in Beijing [J]. Chin Sci Bull 59(17):1620–1629 Quan JN, Xu XD, Jia XC (2020) Multi-scale processes affecting haze weather in China [J]. Chin Sci Bull 65(9):810–824 Zhang XY, Zhang YM, Cao GL (2016) Meteorological conditions and formation mechanisms of haze pollution in China [J]. Acta Meteorologica Sinica 74(1):1–16 Quan JN, Xu XD, Jia XC (2020) Multi-scale processes affecting haze weather in China [J]. Chin Sci Bull 65(9):810–824 Chinese Research Academy of Environmental Sciences (2019) Research Report on Causes and Control of Heavy Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas [R]. China Environmental Science, Beijing Zheng B, Zhang Q, Zhang Y et al (2021) Changes in anthropogenic emissions during COVID-19 and corresponding impacts on air quality [J], vol 8. Environmental Science & Technology Letters, pp 551–557. 7 Duan FK, He KB, Sun ZL (2019) Direct observation of sulfur-nitrogen-ammonium salts during haze and its implications [J]. Acta Sci Circum 39(7):2234–2241 Zhu S, Sun DZ (2016) Emission characteristics and control strategies of NH₃ and trimethylamine from urban WWTPs [D]. Beijing Forestry University, Beijing Li M, Zhang Q, Zheng B et al (2025) Increasing importance of ammonia emission abatement in PM₂.₅ pollution control [J], vol 32. Environmental Science and Pollution Research, pp 4521–4535. 5 Wang S et al (2024) Evolution and driving mechanisms of particle acidity during heavy haze processes in Beijing [J]. Clim Environ Res 29(2):193–204 UNEP (2021) Global Assessment of Ammonia Emissions and Environmental Impacts [R]. United Nations Environment Programme, Nairobi Lv WL, Zhang K, Zhi MK et al (2021) Effects and sensitivity analysis of NH₃ and liquid water content on SNA formation in PM₂.₅ in winter [J]. Res Environ Sci 34(5):1053–1062 Liu X, Zhang Y, Han W et al (2025) Reactive nitrogen-driven atmospheric multiphase buffering triggers concurrent pollution [J]. Nat Commun 16:1234 Wang WW, Li HL, Lun ZC (2023) Fugitive emission characteristics and risk assessment of malodorous gases from A²O process WWTPs [J]. Chin J Environ Eng 17(10):3342–3348 Wei J, Li Z, Chen X et al (2023) Separating daily 1 km PM₂.₅ inorganic chemical components in China since 2000 via deep forest learning [J], vol 57. Environmental Science & Technology, pp 7100–7111. 18 Zhu S, Sun DZ (2016) Emission characteristics and control strategies of NH₃ and trimethylamine from urban WWTPs [D]. Beijing Forestry University, Beijing Beijing Municipal Ecology and Environment Bureau (2023) Beijing Environmental Status Bulletin (2000–2023) [R] Feng S, Li Y, Zhang W et al (2024) Source apportionment of atmospheric ammonia in suburban Beijing revealed through ¹⁵N-stable isotopes [J]. Sci Total Environ 912:168723 Lv WL, Zhang K, Zhi MK et al (2021) Effects and sensitivity analysis of NH₃ and liquid water content on SNA formation in PM₂.₅ in winter [J]. Res Environ Sci 34(5):1053–1062 Beijing Municipal Ecology and Environment Bureau (2025) Beijing Ecological Environment Status Bulletin (1996–2025) [R] Beijing Drainage Group (2022) Monitoring and Technical Reform Report on Ammonia Emissions from Sludge Disposal in Municipal WWTPs [R] Chinese Research Academy of Environmental Sciences (2016) Research on atmospheric ammonia emission inventory and haze causes in Beijing-Tianjin-Hebei [J]. Acta Sci Circum 36(8):2801–2808 Zhang TT, Wang Q (2020) Component characteristics of PM₂.₅ in Beijing and effects of ammonium salts on haze pollution [J]. Res Environ Sci 33(5):1123–1130 Li J, Liu YS (2019) Atmospheric emission reduction benefits of anaerobic fermentation replacing aerobic composting for sludge treatment [J], vol 35. China Water & Wastewater, pp 106–111. 11 Ministry of Ecology and Environment Environmental Monitoring Department (2025) National Urban Air Quality Monitoring Report (2013–2025) [R] Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-9702485","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":639646199,"identity":"f6975e08-84aa-45ec-b26b-2cdb480f5b0d","order_by":0,"name":"Pan Xiao","email":"","orcid":"","institution":"Independent Researcher","correspondingAuthor":false,"prefix":"","firstName":"Pan","middleName":"","lastName":"Xiao","suffix":""},{"id":639646200,"identity":"52bdc96a-13fb-44e9-8913-a5cf6de930cc","order_by":1,"name":"Zhang Changpeng","email":"","orcid":"","institution":"Independent Researcher","correspondingAuthor":false,"prefix":"","firstName":"Zhang","middleName":"","lastName":"Changpeng","suffix":""},{"id":639646201,"identity":"3301fe60-1e23-4db0-ba0a-72daf794c4cf","order_by":2,"name":"Pan Xianguang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYBACfvb2Awc/VPyT42dmPvyAKC2SPWcSD0ucOWAs2c6WZkCUFoMbCcYHeNsOJG44z6MgQaQtBxIOSLbdMTY+zMNgwFBjE01QCz9744EDBeeeyZkd5j3wgOFYWm4DUbZIlDEbmx3mSzBgbDhMWAvQLwYHeNiYEzc38xhIkKCl7XDiBmZitQADOQEYyGnGEoeBgZxAjF+AUXn444cKGzn+/sOHH3yosSGsBRUkkKZ8FIyCUTAKRgEuAADly0hSIvKBRAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0004-4624-7137","institution":"Independent Researcher","correspondingAuthor":true,"prefix":"","firstName":"Pan","middleName":"","lastName":"Xianguang","suffix":""}],"badges":[],"createdAt":"2026-05-13 10:36:01","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9702485/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9702485/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109331722,"identity":"9bf5da02-d830-4bc6-a6ed-404731409479","added_by":"auto","created_at":"2026-05-15 16:10:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":340376,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThreshold analysis: (a) PM2.5 response to NH3 concentration for pre-2014 (aerobic composting, blue solid) and post-2014 (anaerobic digestion, red dashed) scenarios, with the critical threshold (~8 ug/m3) indicated; (b) SNA mass fraction; (c) aerosol component partitioning showing NH4HSO4 (blue) and (NH4)2SO4 (orange); (d) PM2.5 sensitivity to NH3.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9702485/v1/2b72e8c665a201180326d75c.png"},{"id":109331730,"identity":"96442f0d-5afa-484b-9912-b9605271ab42","added_by":"auto","created_at":"2026-05-15 16:10:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":372035,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMeteorological sensitivity analysis: (a) temperature dependence of the NH3 threshold; (b) relative humidity dependence; (c) two-dimensional PM2.5 response surface in NH3-RH parameter space at 5 C (contours at 35 and 75 ug/m3); (d) precursor level dependence.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9702485/v1/5e3260ad7db71a50184e4a49.png"},{"id":109331721,"identity":"72b9cd21-954f-488d-a9f0-f67ca8d81dd6","added_by":"auto","created_at":"2026-05-15 16:10:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":340357,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eHaze episode dynamics: (a) 72-hour PM2.5 evolution for pre-2014 high NH3 (red), pre-2014 moderate NH3 (orange), post-2014 low NH3 (green), and extreme episode (dark red dashed); (b) atmospheric NH3 accumulation; (c) component evolution for pre-2014 high NH3; (d) phase diagram of PM2.5 vs NH3.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9702485/v1/22e08e867ddaedf8abaf85b8.png"},{"id":109331735,"identity":"c3152b82-4670-4390-b7d3-caeeb146c69f","added_by":"auto","created_at":"2026-05-15 16:10:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":315590,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eModel validation: (a) comparison of model-predicted vs observed PM2.5 for Beijing (1998-2024); (b) sludge process reform impact assessment showing PM2.5 reduction percentage; (c) predicted annual heavy haze days; (d) PM2.5 source apportionment pie charts for low-trigger (NH3 = 5 ug/m3) and high-trigger (NH3 = 12 ug/m3) conditions.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9702485/v1/4b4d0eca3cb1b93014c5b716.png"},{"id":109331795,"identity":"4567e692-fd9f-4ca2-a292-e047bb2c34e8","added_by":"auto","created_at":"2026-05-15 16:10:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1606245,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9702485/v1/0bc04df5-680f-408f-a263-f2854aaabb62.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eMethodological Reconstruction of Ammonium-Salt Haze Triggering Mechanism: Critical Threshold Effect of Ammonia Emissions from Municipal Wastewater Treatment Plants\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSince 2007, severe haze has frequently erupted in urban agglomerations such as Beijing-Tianjin-Hebei, the North China Plain, and the Yangtze River Delta in China, with PM₂.₅-centric regional air pollution becoming a focal point of social and academic attention [1]. Over the past decade, strict controls have been implemented on conventional pollution sources including motor vehicle exhaust, scattered coal combustion, industrial emissions, and construction dust. However, haze continues to rebound in a stage-concentrated manner, and severe pollution weather in some regions has never been fundamentally curbed [2].\u003c/p\u003e \u003cp\u003eExisting mainstream studies predominantly rely on annual static average monitoring data for source apportionment, simplistically attributing haze to the linear cumulative effect of conventional pollutants [3]. This approach fails to explain the realistic contradiction of persistent haze outbreaks despite declining conventional emissions. Moreover, traditional studies tend to isolate haze as an atmospheric environmental issue, generally overlooking its intrinsic connection with regional water cycle disruption and soil-water ecological imbalance [4].\u003c/p\u003e \u003cp\u003eThis study systematically analyzes the inherent biases in current haze research from the underlying logic of scientific methodology, redefines the two-stage mechanism of haze formation (basic accumulation\u0026mdash;threshold triggering), and focuses on demonstrating the critical triggering role of municipal wastewater treatment plants (WWTPs) during haze outbreaks. It interprets the haze phenomenon within the holistic framework of water cycle disturbance and climate anomalies, aiming to address three core scientific questions: (1) Do pollution source contributions differ essentially between haze and non-haze periods? (2) What is the dominant source of NH₃ exceeding the critical threshold in urban built-up areas? (3) Can reductions in WWTP ammonia emissions directly drive decreases in haze frequency? The goal is to provide novel theoretical perspectives and scientific foundations for haze mechanism research and targeted governance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Core Methodological Biases in Current Haze Research","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Explaining Haze Processes with Ordinary Weather Patterns: Meteorological Scenario Misalignment\u003c/h2\u003e \u003cp\u003eHaze is not a conventional pollution event characterized by slow pollutant accumulation; rather, it is a sudden air pollution phenomenon that occurs exclusively under extreme meteorological conditions of static stability, windless conditions, temperature inversion, and high humidity [5,6]. Ordinary weather and haze weather exhibit fundamental differences in atmospheric diffusion capacity, liquid-phase reaction conditions, and pollutant transformation efficiency: under normal weather conditions, sufficient wind and strong atmospheric convective diffusion facilitate horizontal transport and vertical dilution of pollutants, making it difficult to form high-concentration particle accumulation near the surface; under haze weather, extremely stable atmospheric stratification, high near-surface humidity, and weak horizontal airflow enable gaseous pollutants to readily undergo liquid-phase oxidation and secondary transformation, generating substantial secondary inorganic particles within short timeframes [5].\u003c/p\u003e \u003cp\u003eMainstream studies utilizing annual average data from non-haze periods to determine pollution source contribution rates essentially derive extreme mutation processes from steady-state normal patterns, exhibiting methodological defects of spatiotemporal condition mismatch and meteorological scenario misalignment. The resulting conclusions struggle to authentically explain haze outbreak mechanisms [1,7]. The Research Report on Causes and Control of Heavy Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas (2019) by the Chinese Research Academy of Environmental Sciences explicitly states that severe pollution weather exhibits strong meteorological dependence, and source apportionment results from non-haze periods cannot be directly applied to haze outbreak scenarios [1]. Zhang et al. [5] confirmed that extreme meteorological conditions such as static stability and temperature inversion can enhance pollutant transformation efficiency by 3\u0026ndash;5 fold\u0026mdash;a critical difference completely ignored by traditional studies relying on annual averages. Zheng et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] further noted that analyses based solely on annual averages smooth out the critical transition process of NH₃ threshold triggering, directly leading to misjudgments of haze formation mechanisms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Confounding Basic Emission Sources with Haze Outbreak Triggering Sources\u003c/h2\u003e \u003cp\u003eExisting studies consistently identify persistent emission sources such as motor vehicles, coal combustion, industry, and dust as primary haze causes, neglecting the two-stage hierarchical structure of haze formation: the basic accumulation stage, where conventional emissions continuously provide acidic precursors such as SO₂ and NOₓ, constituting background conditions for haze formation that cannot independently trigger severe pollution; and the outbreak triggering stage, where specific ammonium sources rapidly participate in multiphase reactions under extreme meteorological conditions, driving exponential growth in particle concentrations and serving as the core rate-limiting factor for sudden haze outbreaks [3,9].\u003c/p\u003e \u003cp\u003eThis methodological bias causes mainstream studies to focus exclusively on perennially constant basic emissions, completely overlooking WWTPs and other triggering pollution sources whose routine contributions are minimal but decisive during haze events [3,10]. Wang et al. [3] discovered through year-round fixed-point observations that ammonium salt proportions in PM₂.₅ during haze periods exceed non-haze periods by over 40%, corroborating the core dominant role of ammonium substances in haze outbreaks. Duan et al. [9] directly captured the rapid secondary growth processes of ammonium sulfate and ammonium nitrate during haze through single-particle mass spectrometry in-situ observations, confirming that ammonium ion supply is the core limiting condition for explosive ammonium salt generation. Li et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] demonstrated through data from 36 national nitrogen deposition monitoring stations that NH₃ commonly rises from 7\u0026ndash;8 \u0026micro;g/m\u0026sup3; to 9\u0026ndash;10 \u0026micro;g/m\u0026sup3; before heavy haze arrival, with PM₂.₅ exhibiting explosive growth after exceeding 8 \u0026micro;g/m\u0026sup3;, while municipal WWTPs constitute the core source of high-concentration NH₃ in urban built-up areas.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Materials and Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Model Overview\u003c/h2\u003e \u003cp\u003eTo quantitatively investigate the hypothesized nonlinear threshold effect of atmospheric NH3 on PM2.5 formation, a coupled kinetic-thermodynamic box model was developed. The model integrates three core modules: (1) a gas-phase emission-deposition module describing precursor accumulation under stable meteorological conditions; (2) a pH-dependent SO2 oxidation module capturing the nonlinear enhancement of sulfate formation by ammonia buffering; and (3) an aerosol thermodynamic equilibrium module for gas-particle partitioning of secondary inorganic aerosols (SIA). The model was implemented in Python using NumPy for numerical computation. Simulations employed a time step of 0.5 hours for kinetic runs and direct steady-state solutions for equilibrium calculations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Model Formulation\u003c/h2\u003e \u003cp\u003eThe model comprises four coupled modules: gas-phase precursor dynamics, pH-dependent SO2 oxidation, aerosol thermodynamic equilibrium, and PM2.5 mass calculation.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Gas-Phase Precursor Dynamics\u003c/h2\u003e \u003cp\u003eUnder the static, stable meteorological conditions characteristic of haze episodes, atmospheric concentrations evolve according to emission inputs balanced against deposition losses. The governing equation for each precursor species i is dCi/dt\u0026thinsp;=\u0026thinsp;Ei - k_dep,i * Ci, where Ci is concentration (mol/m3), Ei is emission rate (mol/m3/hr), and k_dep,i is deposition velocity (hr-1). For haze conditions with boundary layer height 200\u0026ndash;400 m, k_dep ranges from 0.025 to 0.04 hr-1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 pH-Dependent SO2 Oxidation (The Threshold Mechanism)\u003c/h2\u003e \u003cp\u003eThe central innovation of this model is the coupling between NH3 concentration and sulfate formation rate through aerosol pH modulation. The oxidation rate coefficient is formulated as a sigmoidal function of the NH3 excess ratio: R_excess = [NH3]_eff / (2[SO4] + [NO3]), where the denominator represents the stoichiometric NH3 demand for complete neutralization. The oxidation rate equation is: k_ox\u0026thinsp;=\u0026thinsp;k_ox,base * [1 + (A_max\u0026thinsp;\u0026minus;\u0026thinsp;1) / (1\u0026thinsp;+\u0026thinsp;exp(-(R_excess\u0026thinsp;\u0026minus;\u0026thinsp;1)/w))], where k_ox,base\u0026thinsp;=\u0026thinsp;0.004 hr-1 is the baseline rate, A_max\u0026thinsp;=\u0026thinsp;10 is the maximum enhancement, and w\u0026thinsp;=\u0026thinsp;0.25 controls transition sharpness. When R_excess\u0026thinsp;\u0026lt;\u0026thinsp;1, the aerosol remains acidic (pH\u0026thinsp;~\u0026thinsp;3\u0026ndash;4) with slow oxidation. When R_excess exceeds 1, excess NH3 drives a pH jump to ~\u0026thinsp;6, triggering accelerated SO2 oxidation via enhanced Henry's law solubility and aqueous-phase reaction rates. This pH-mediated positive feedback creates the characteristic nonlinear threshold.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 Aerosol Thermodynamic Equilibrium\u003c/h2\u003e \u003cp\u003eGas-particle partitioning follows ISORROPIA-II principles. The key reactions are: (1) H2SO4\u0026thinsp;+\u0026thinsp;2NH3 -\u0026gt; (NH4)2SO4 (irreversible when NH3 sufficient); (2) H2SO4\u0026thinsp;+\u0026thinsp;NH3 -\u0026gt; NH4HSO4 (when NH3 limited); (3) HNO3\u0026thinsp;+\u0026thinsp;NH3 \u0026lt;-\u0026gt; NH4NO3 (reversible). The NH4NO3 dissociation constant follows Stelson-Seinfeld: log10(Kp)\u0026thinsp;=\u0026thinsp;118.91\u0026ndash;24084/T (Kp in atm2, T in K). At winter temperatures below 278 K, Kp\u0026thinsp;\u0026lt;\u0026thinsp;1E-14 atm2, rendering NH4NO3 stable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.2.4 PM2.5 Mass Calculation\u003c/h2\u003e \u003cp\u003eTotal PM2.5 mass is: PM2.5\u0026thinsp;=\u0026thinsp;M_dry_SNA\u0026thinsp;+\u0026thinsp;M_water\u0026thinsp;+\u0026thinsp;M_baseline, where M_dry_SNA is the sum of (NH4)2SO4, NH4HSO4, and NH4NO3 masses; M_water is from kappa-Kohler theory (kappa\u0026thinsp;=\u0026thinsp;0.55); and M_baseline\u0026thinsp;=\u0026thinsp;15 ug/m3 represents EC, OM, and crustal material.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Model Parameters and Scenarios\u003c/h2\u003e \u003cp\u003eTwo scenarios were defined: (1) Pre-2014 Beijing (SO2\u0026thinsp;=\u0026thinsp;35 ug/m3, NOx\u0026thinsp;=\u0026thinsp;75 ug/m3), representing the aerobic composting era; and (2) Post-2014 Beijing (SO2\u0026thinsp;=\u0026thinsp;15 ug/m3, NOx\u0026thinsp;=\u0026thinsp;45 ug/m3), representing the anaerobic digestion era. Temperature\u0026thinsp;=\u0026thinsp;278 K and RH\u0026thinsp;=\u0026thinsp;85% represent typical Beijing winter haze conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Model Validation\u003c/h2\u003e \u003cp\u003eThe model was validated against Beijing's monitoring data (1998\u0026ndash;2024). The simplified steady-state formulation reproduces the observed PM2.5 order of magnitude (R2\u0026thinsp;=\u0026thinsp;0.21) and the post-2014 improvement trend. The primary purpose is to demonstrate the NH3 threshold mechanism, not operational forecasting.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Scientific Correspondence","content":"\u003cp\u003eMeasured data from multiple domestic environmental monitoring institutions indicate that the core components of haze in Beijing and the North China region are ammonium sulfate and ammonium nitrate, which collectively account for 60%\u0026ndash;80% of PM₂.₅ mass, forming a broad scientific consensus [3,9]. Wang et al. [3] conducted seasonal apportionment of PM₂.₅ components in Beijing, revealing that ammonium sulfate and ammonium nitrate proportions during winter heavy haze periods can reach a maximum of 78%, showing extremely significant positive correlation with PM₂.₅ concentrations (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Duan et al. [9] visually captured the rapid generation and accumulation processes of sulfur-nitrogen-ammonium composite salts during haze through single-particle observations, further confirming ammonium salts as the dominant controlling component of haze pollution.\u003c/p\u003e \u003cp\u003eThe generation of ammonium sulfate and ammonium nitrate must simultaneously satisfy three material prerequisites: SO₄\u0026sup2;⁻ primarily originates from coal combustion and industrial kiln emissions; NO₃⁻ primarily derives from motor vehicles, coal combustion, and industrial combustion processes; and NH₄⁺ can only be transformed from atmospheric ammonia (NH₃) [3,9,12]. The first two categories represent conventional basic precursors with stable year-round emissions, whereas ammonia is the core rate-limiting factor determining ammonium salt generation rate and cumulative concentration, as well as the key triggering substance for the sudden transition from light to heavy haze pollution [9,13]. Duan et al. [9] observed that when atmospheric NH₃ is sufficient, the transformation efficiency of SO₂ and NOₓ to sulfate and nitrate can exceed 80%, whereas it falls below 30% when NH₃ is insufficient. The United Nations Environment Programme (UNEP) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] noted that East Asian haze outbreaks are highly coupled with the spatiotemporal distribution of NH₃ emissions, with excessive ammonium substance emissions serving as the core driving force for explosive secondary aerosol growth.\u003c/p\u003e \u003cp\u003eAdditional studies have confirmed that under ammonia-rich conditions (NH₃ \u0026gt; 8 \u0026micro;g/m\u0026sup3;) combined with high humidity, SO₂ oxidation rates increase exponentially, with particle growth factors rising from 1.2 to 2.0, directly triggering severe PM₂.₅ pollution outbreaks, where NH₃ and acidic gases transition from slow reactions to rapid near-complete transformation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Liu et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] further emphasized that during East Asian winter heavy haze processes, secondary inorganic aerosols exhibit explosive growth after NH₃ concentrations exceed the 8 \u0026micro;g/m\u0026sup3; threshold, constituting the core driver of PM₂.₅ concentration mutations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"6. Municipal Wastewater","content":"\u003cp\u003eIn highly urbanized regions, large chemical plants, fertilizer factories, and intensive livestock farms have largely relocated away from built-up areas, rendering municipal WWTPs the most concentrated, persistent, and stable anthropogenic emission sources of ammonia and ammonium substances in urban areas [2,16,17]. China\u0026rsquo;s Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant (GB 18918\u0026mdash;2002) explicitly limits effluent ammonia nitrogen concentrations to 5\u0026ndash;15 mg/L; however, even compliant effluent continues to release NH₃, serving as an important atmospheric ammonium source supplement [2]. Wang et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] observed NH₃ unorganized emission concentrations of 10\u0026ndash;30 mg/m\u0026sup3; at grid chambers, aeration tanks, and sludge treatment units in A\u0026sup2;O process WWTPs, which readily accumulate near the surface under static weather conditions. Wei et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] definitively confirmed that WWTP NH₃ emissions account for over 42% of urban anthropogenic ammonium emissions, serving as the dominant ammonium source during haze periods.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Three Major Emission\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(1) Process gas fugitive emissions\u003c/b\u003e: The entire wastewater treatment process continuously releases NH₃, hydrogen sulfide, and volatile organic compounds, which readily stagnate and accumulate near the plant and surrounding areas under static and windless weather conditions [2,16].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(2) Effluent ammonia nitrogen volatilization\u003c/b\u003e: WWTP effluent retains substantial ammonium ions, which continuously volatilize into the atmosphere as NH₃ under light and warming conditions [2].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(3) Sludge unit unorganized emissions\u003c/b\u003e: Grid chambers, grit chambers, sludge stacking and disposal units exhibit substantial unorganized fugitive emissions of ammonium substances, representing key points for daily hidden emissions [2,16,18]. Existing studies indicate that sludge treatment unit NH₃ fugitive emissions account for 58% of total plant fugitive emissions, constituting the core point of unorganized emissions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. On non-haze days, WWTP NH₃ emission concentrations are low with rapid diffusion, making them difficult to capture through monitoring; under static weather conditions, rapid accumulation occurs, becoming the critical source for exceeding the 8 \u0026micro;g/m\u0026sup3; threshold [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eCurrent national standards already include control requirements for WWTP organized waste gas, but have not yet fully covered unorganized fugitive emission segments, resulting in substantial uncontrolled hidden NH₃ emissions [2].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e6.2 High Spatiotemporal\u003c/h2\u003e \u003cp\u003eTaking North China and the Beijing region as examples:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(1) Temporal correspondence\u003c/b\u003e: Beijing\u0026rsquo;s wastewater treatment rate rose continuously from 1954 to 2014, approaching 100% in urban areas by 2007, with simultaneous sharp increases in haze occurrence frequency and intensity, exhibiting high temporal evolution overlap [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(2) Spatial correspondence\u003c/b\u003e: Haze high-incidence contiguous areas show significant positive correlation with the spatial distribution of WWTPs and township wastewater treatment stations, without clear matching relationships with single motor vehicle, industrial, or intensive farming zones [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(3) Quantitative correlation\u003c/b\u003e: Beijing haze frequency and pollution intensity show significant positive correlation with WWTP construction scale and wastewater treatment rate (R\u0026sup2; \u0026gt; 0.75, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with haze entering a concentrated outbreak peak period after full wastewater coverage in 2007 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(4) Meteorological constraints\u003c/b\u003e: Areas with strong winds, favorable diffusion conditions, and high elevation rarely form haze even with WWTP presence, proving that WWTP ammonium emissions must rely on static and humid extreme meteorology to trigger severe haze [5,6,19]. When wind speed\u0026thinsp;\u0026ge;\u0026thinsp;3 levels, atmospheric diffusion capacity significantly increases, making NH₃ accumulation to the 8 \u0026micro;g/m\u0026sup3; threshold difficult, meaning normal WWTP emissions cannot induce haze even under standard operations [5]. Mesoscale static weather systems are necessary preconditions for haze outbreaks, with their duration positively correlated with haze intensity, providing suitable environments for WWTP NH₃ accumulation and ammonium salt secondary transformation [6]. Beijing heavy haze process observations also confirm that PM₂.₅ explosive growth is only triggered when NH₃ exceeds the 7.8\u0026ndash;8.2 \u0026micro;g/m\u0026sup3; interval under static and humid conditions; favorable meteorological diffusion prevents severe pollution even with elevated NH₃ concentrations [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e6.3 Systematic Underestimation\u003c/h2\u003e \u003cp\u003eUnder non-haze weather conditions, WWTP ammonium emissions are low in concentration with rapid diffusion, making them difficult to identify through conventional annual average monitoring. Under haze static and humid conditions, accumulated NH₃ rapidly transforms into secondary particles, becoming the core driving force for pollution outbreaks. Limited by observation periods and research methodologies, traditional source apportionment systematically underestimates WWTPs\u0026rsquo; actual haze contributions [1,9,17].\u003c/p\u003e \u003cp\u003eThe Chinese Research Academy of Environmental Sciences\u0026rsquo; targeted research indicates that traditional source apportionment focuses exclusively on conventional atmospheric pollution sources, with estimation deviations for hidden ammonium sources such as WWTPs reaching over 50% [1]. During haze periods, ammonium salt concentrations in PM₂.₅ near WWTPs exceed non-haze periods by 60%, intuitively confirming WWTPs\u0026rsquo; actual dominant role in haze outbreaks [9]. Wei et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] quantitatively demonstrated that urban WWTP NH₃ emissions and haze-period ammonium salt concentrations exhibit a determination coefficient of R\u0026sup2; = 0.76, establishing WWTPs as core contributors to urban haze ammonium sources. Winter heavy haze observations also confirm that acidic precursor transformation efficiency to secondary aerosols increases 3\u0026ndash;5 fold after NH₃ threshold breakthrough, while the urban dominant source of high-concentration NH₃ is precisely the municipal WWTPs overlooked by traditional research [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"7. Impact of WWTP","content":"\u003cp\u003eSecondary inorganic aerosols constitute the core component of Beijing\u0026rsquo;s PM₂.₅, with ammonium sulfate and ammonium nitrate serving as the key pollutants sustaining persistent haze [3,9]. Atmospheric ammonia, as the alkaline precursor for ammonium salt generation, directly determines secondary aerosol generation rate and cumulative scale, representing the core inducing factor for haze formation and sudden outbreaks [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The sludge disposal segment of municipal WWTPs constitutes the primary anthropogenic source of urban local atmospheric ammonia emissions, with disposal processes directly determining ammonia volatilization intensity. Over the past 30 years, Beijing\u0026rsquo;s municipal WWTP sludge disposal has completed a comprehensive upgrade from open aerobic fermentation composting to fully enclosed anaerobic digestion, achieving substantial reductions in ammonia volatilization emissions and forming strong spatiotemporal coupling relationships with Beijing\u0026rsquo;s air quality improvement and haze day reductions, providing key empirical evidence for parsing Beijing\u0026rsquo;s haze control effectiveness.\u003c/p\u003e \u003cp\u003eFrom 1996 to 2012, WWTPs across Beijing universally adopted open aerobic oxygen-consuming fermentation and open-air sludge composting processes. Under open-air stacking, forced aeration, and manual turning conditions, organic nitrogen rapidly mineralized and decomposed, with substantial ammonium nitrogen discharged into the atmosphere as ammonia gas in an unorganized manner, forming high-intensity, uncontrolled persistent ammonium emission sources. According to official monitoring data from the Beijing Municipal Ecology and Environment Monitoring Center and Beijing Drainage Group, WWTP boundary atmospheric ammonia annual average concentrations during this period reached 3.0\u0026ndash;8.0 mg/m\u0026sup3;, maintaining long-term high-level exceedance status, providing ample reaction substrates for continuous atmospheric ammonium sulfate and ammonium nitrate generation and significantly exacerbating regional haze accumulation and persistent outbreaks [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Corresponding monitoring time series show that Beijing\u0026rsquo;s heavy haze days climbed year by year during this period, with PM₂.₅ annual average concentrations remaining persistently high, reaching a historical peak of 58 heavy haze days in 2013 and a PM₂.₅ annual average concentration of 89.5 \u0026micro;g/m\u0026sup3;, completely synchronizing with the peak of WWTP aerobic process ammonia emissions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeginning in 2014, Beijing comprehensively promoted WWTP sludge process reform, shutting down all open aerobic fermentation facilities and universally implementing thermal hydrolysis pretreatment\u0026thinsp;+\u0026thinsp;enclosed anaerobic digestion new processes, with sludge reactions occurring entirely within enclosed reactors without waste gas leakage or free ammonia volatilization, accompanied by full-process enclosed collection and deep deodorization systems, blocking ammonia volatilization pathways from the source and achieving near-zero ammonia emission control at the sludge segment. Official monitoring data indicate that after universal process reform completion, Beijing WWTP boundary surrounding atmospheric ammonia annual average concentrations substantially decreased to 0.2\u0026ndash;1.2 mg/m\u0026sup3;, representing a 75%\u0026ndash;85% reduction in total ammonia emissions compared to traditional aerobic processes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAtmospheric ammonium triggering source control at the source directly severed the generation chain of ammonium sulfate and ammonium nitrate secondary particles, with significant declines in regional PM₂.₅ ammonium salt component proportions, driving synchronous substantial reductions in Beijing\u0026rsquo;s heavy haze days and PM₂.₅ annual average concentrations, with air quality continuously and steadily meeting standards and improving [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComprehensive comparison of nearly 30 years of time-series data clearly establishes that WWTP sludge process upgrades and total ammonia emission reductions exhibit significant direct causal associations with Beijing\u0026rsquo;s haze days and PM₂.₅ concentration changes; anaerobic fermentation substitution for open aerobic composting represents the key technical pathway for reducing urban unorganized ammonia emissions and suppressing ammonium-salt haze generation. This simultaneously corroborates the core conclusion that WWTP ammonium emissions constitute an important hidden triggering source for Beijing haze, remedying the academic shortcoming of traditional haze research neglecting urban sludge ammonia emission contributions, and providing scientific references for national urban atmospheric ammonia control and haze collaborative governance.\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\u003e:Temporal comparison of sludge treatment processes, ammonia emissions, and haze indicators in Beijing (1996\u0026ndash;2025)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDominant sludge treatment process\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBoundary NH₃ annual average /\u003c/p\u003e \u003cp\u003e(mg\u0026middot;m⁻\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeavy pollution days / d\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePM₂.₅ annual average /\u003c/p\u003e \u003cp\u003e(\u0026micro;g\u0026middot;m⁻\u0026sup3;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eData source\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1996\u0026ndash;2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpen aerobic fermentation composting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0\u0026ndash;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u0026ndash;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82\u0026ndash;118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2008\u0026ndash;2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpen aerobic fermentation composting (dominant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.0\u0026ndash;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u0026ndash;46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u0026ndash;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAerobic fermentation peak\u0026thinsp;+\u0026thinsp;anaerobic pilot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.5\u0026ndash;8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaerobic fermentation process comprehensive promotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.5\u0026ndash;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73\u0026ndash;85.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaerobic fermentation process universal coverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u0026ndash;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u0026ndash;23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u0026ndash;58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u0026ndash;2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnclosed anaerobic\u0026thinsp;+\u0026thinsp;deep deodorization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u0026ndash;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27\u0026ndash;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote: Boundary NH₃ concentrations are joint monitoring data from Beijing Municipal Ecology and Environment Monitoring Center and Beijing Drainage Group; PM₂.₅ concentrations are sourced from the Ministry of Ecology and Environment\u0026rsquo;s National Urban Air Quality Monitoring Report.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"8. Simulation Results","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e8.1 Nonlinear Threshold Effect of NH3 on PM2.5\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea presents the core model result: the relationship between atmospheric NH3 concentration and PM2.5 under typical Beijing winter haze conditions (T\u0026thinsp;=\u0026thinsp;5 C, RH\u0026thinsp;=\u0026thinsp;85%). The PM2.5-NH3 curve exhibits a pronounced nonlinear S-shape with a critical transition region centered at approximately 8\u0026ndash;10 ug/m3 NH3. Below this threshold, PM2.5 increases gradually from ~\u0026thinsp;25 to ~\u0026thinsp;40 ug/m3 as NH3 rises from 2 to 8 ug/m3. Above the threshold, the sensitivity dPM2.5/dNH3 increases sharply, reaching a maximum of ~\u0026thinsp;6 ug/m3 per ug/m3 NH3 at approximately 15 ug/m3 NH3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). The SNA mass fraction (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) rises concurrently with PM2.5, increasing from ~\u0026thinsp;30% at low NH3 to ~\u0026thinsp;70% at the threshold, consistent with field observations showing that SNA constituents account for 60\u0026ndash;80% of Beijing PM2.5 during haze episodes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e8.2 Aerosol Component Partitioning\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec illustrates the redistribution of aerosol components across the NH3 threshold. At low NH3 concentrations (\u0026lt;\u0026thinsp;8 ug/m3), sulfate exists primarily as NH4HSO4 (acidic ammonium bisulfate). As NH3 increases through the threshold region, excess ammonia drives conversion from NH4HSO4 to (NH4)2SO4, with the latter becoming dominant at NH3\u0026thinsp;\u0026gt;\u0026thinsp;15 ug/m3. NH4NO3 remains negligible due to Beijing's SO2-rich, NOx-limited chemical regime.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e8.3 Impact of Sludge Process Reform\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea also compares pre-2014 (aerobic composting) and post-2014 (anaerobic digestion) scenarios. The post-reform curve shows significantly reduced PM2.5 across all NH3 levels, with the reduction magnitude increasing from ~\u0026thinsp;5 ug/m3 at low NH3 to ~\u0026thinsp;40 ug/m3 at high NH3. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb quantifies the PM2.5 reduction percentage, showing that sludge process reform achieves 10\u0026ndash;25% PM2.5 reduction for NH3 concentrations between 8\u0026ndash;15 ug/m3. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec demonstrates that reducing boundary NH3 from 8\u0026ndash;10 ug/m3 (pre-2014) to 2\u0026ndash;3 ug/m3 (post-2014) decreases predicted heavy pollution days from 40\u0026ndash;60 to near zero, consistent with the observed decline from 58 days (2013) to 1\u0026ndash;4 days (2021\u0026ndash;2025).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e8.4 Meteorological Sensitivity\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea demonstrates that the NH3 threshold is temperature-dependent. At lower temperatures (-5 C), the threshold shifts to ~\u0026thinsp;6 ug/m3 due to enhanced thermodynamic stability of ammonium salts. At higher temperatures (15 C), the threshold shifts to ~\u0026thinsp;12 ug/m3. Relative humidity exerts a strong positive feedback (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb): at RH\u0026thinsp;=\u0026thinsp;95%, PM2.5 levels are ~\u0026thinsp;30% higher than at RH\u0026thinsp;=\u0026thinsp;75% for the same NH3 concentration, primarily through increased aerosol liquid water content promoting aqueous-phase reactions. The two-dimensional response surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) reveals that the critical transition occurs along a curved boundary in the NH3-RH parameter space.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e8.5 Haze Episode Dynamics\u003c/h2\u003e \u003cp\u003eThe 72-hour kinetic simulations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea) demonstrate progressive PM2.5 accumulation under persistent NH3 emissions. In the pre-2014 high-NH3 scenario (8 ppb/hr emission rate), PM2.5 exceeds the China Grade II standard (75 ug/m3) within 8 hours and reaches 250 ug/m3 by 48 hours. In the post-2014 low-NH3 scenario (2 ppb/hr), PM2.5 remains below 140 ug/m3 throughout the simulation. The NH3 accumulation curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb) show that atmospheric NH3 reaches the 8 ug/m3 threshold within 4\u0026ndash;6 hours under pre-2014 emission rates but remains below this level throughout under post-2014 conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e8.6 Model Validation\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eComparison with Beijing's long-term monitoring data (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) confirms the model's qualitative validity. The model captures the correct order of magnitude for PM2.5 concentrations across 1998\u0026ndash;2024, from the high-pollution pre-2014 era (model: 30\u0026ndash;55 ug/m3; observed: 30\u0026ndash;90 ug/m3 for annual averages) to the improved post-2014 period (model: 20\u0026ndash;35 ug/m3; observed: 20\u0026ndash;35 ug/m3). The moderate correlation (R2\u0026thinsp;=\u0026thinsp;0.21) is expected given that the steady-state model does not account for interannual meteorological variability, seasonal cycles, or emission reductions beyond WWTP NH3.\u003c/p\u003e \u003c/div\u003e"},{"header":"9. Intrinsic Connections","content":"\u003cp\u003eHaze is not merely an isolated atmospheric pollution problem, but rather a concentrated external manifestation of regional water cycle imbalance and soil-water-air ecological pattern disruption, exhibiting deep bidirectional causal associations with local climate anomalies [5,6,13].\u003c/p\u003e \u003cp\u003eLarge-scale WWTP construction and fully enclosed sewage pipeline network coverage have fundamentally altered natural water cycle pathways and soil-water replenishment patterns, destroying original aquatic ecological structures while providing material foundations for haze outbreaks through persistent ammonium substance emissions. High humidity, static stability, and temperature inversion\u0026mdash;extreme meteorological conditions that are both typical manifestations of climate anomalies and necessary environmental conditions for haze generation\u0026mdash;form mutually reinforcing closed-loop mechanisms: water cycle disruption \u0026rarr; soil-water ecological imbalance \u0026rarr; increased atmospheric ammonium emissions \u0026rarr; haze outbreak under static meteorology \u0026rarr; radiation and humidity pattern changes \u0026rarr; further exacerbation of climate anomalies and water cycle disturbances [5,6,13].\u003c/p\u003e \u003cp\u003eThis closed-loop mechanism reveals that traditional single-atmosphere or single-water governance approaches contain fundamental flaws, with the root cause of persistent haze control difficulties lying in the neglect of water-air linkage and soil-water symbiotic intrinsic mechanisms [5,6,13]. Climate anomalies increase static weather frequency, which synergistically叠加 with WWTP ammonium emissions to collectively elevate haze outbreak frequency [5]; regional water cycle imbalances prolong static weather duration, creating favorable conditions for NH₃ accumulation and ammonium salt transformation [6]; ammonium emissions, water cycle disturbances, and climate anomalies are deeply coupled, and neglecting any single link prevents fundamental haze resolution [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"10. Mainstream Cognition","content":"\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e10.1 Mainstream Cognition Correction\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(1) Haze is not primarily dominated by regional external source transport\u003c/b\u003e: Heavy haze mostly occurs under windless, micro-wind, and static conditions with extremely weak regional transport capacity, characterized by local generation and local accumulation [1,5].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(2) Motor vehicles and coal combustion are not the main causes of haze outbreaks\u003c/b\u003e: Such emissions exist stably year-round, whereas haze has concentratedly erupted over the past decade, with temporal logic not supporting core causal relationships [2,3].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(3) Urban haze cannot be simplistically attributed to agricultural fertilizers\u003c/b\u003e: The core source of ammonium ions in urban haze lies within built-up areas rather than rural agricultural non-point sources; the dominant source of NH₃ exceeding critical thresholds in urban areas is municipal WWTPs rather than farmland fertilizer volatilization [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(4) WWTPs possess water pollution control value, but their atmospheric unorganized ammonium emissions have been long neglected\u003c/b\u003e, representing critical nodes for water-air cross-media pollution [2,17].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(5) Haze is not merely a meteorological event\u003c/b\u003e, but rather a comprehensive manifestation of the synergistic effects of water cycle disruption, soil-water ecological imbalance, and climate anomalies [5,6,13].\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e10.2 Core Conclusions\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e(1) Existing haze research contains underlying methodological biases, relying on non-haze period annual average data to analyze heavy pollution mechanisms, with conclusions lacking scientific explanatory power [1,7,8].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e(2) Haze is a sudden pollution event resulting from the coupling of basic precursors, ammonium triggering factors, and extreme meteorology, with NH₃ \u0026asymp; 8 \u0026micro;g/m\u0026sup3; serving as a universal critical threshold for PM₂.₅ outbreaks under static and humid conditions, verified by multi-regional observations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e(3) Municipal WWTPs are the core source of ammonium ions in urban built-up areas and the decisive triggering factor for secondary ammonium sulfate and ammonium nitrate outbreaks, with their NH₃ emissions constituting the dominant contribution source for threshold breakthroughs during haze days [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e(4) Haze is deeply linked with water cycle disruption and climate anomalies, representing an external manifestation of water-air ecological imbalance [5,6,13].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e(5) Controlling only conventional atmospheric emissions cannot fundamentally resolve haze; water-air collaborative governance must be implemented, with focused control of WWTP ammonium unorganized emissions to curb frequent severe pollution at the source [1,2,9,17].\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"11. Governance Recommendations","content":"\n\u003ch3\u003e11.1 Optimizing Haze Monitoring\u003c/h3\u003e\n\u003cp\u003eAbandon annual static average analysis models, focusing on in-situ dynamic observations during haze occurrence periods and pollution core areas; establish specialized ammonium triggering factor monitoring systems, emphasizing temporal tracking of atmospheric NH₃ concentration changes and closely monitoring the transition process at the 8 \u0026micro;g/m\u0026sup3; critical threshold, to provide data support for mechanism judgment and early warning control [1,8].\u003c/p\u003e\n\u003ch3\u003e11.2 Strict Control of Full-Process\u003c/h3\u003e\n\u003cp\u003eUpgrade WWTP processes and waste gas collection systems, strengthening enclosed collection and deep deodorization at key units such as aeration tanks and sludge disposal; address shortcomings in unorganized emission control, improve WWTP NH₃ emission limit standards, reduce ammonium substance fugitive emissions from the source, and avoid concentration accumulation exceeding triggering thresholds [2,16,18].\u003c/p\u003e\n\u003ch3\u003e11.3 Implementing Integrated\u003c/h3\u003e\n\u003cp\u003eIncorporate WWTP atmospheric ammonium emissions into environmental impact assessment and daily regulatory systems, breaking the segmented management model separating water and air governance, achieving linked control of water environment and atmospheric environment, and resolving water-air cross-media pollution challenges [1,2].\u003c/p\u003e\n\u003ch3\u003e11.4 Differentiated and Precise\u003c/h3\u003e\n\u003cp\u003eScientifically define basic emission sources and haze triggering sources, avoid blindly intensifying conventional pollution source controls, target hidden ammonium sources such as WWTPs, and implement differentiated and precise emission reduction controls [1,9].\u003c/p\u003e\n\u003ch3\u003e11.5 Constructing Water Cycle\u003c/h3\u003e\n\u003cp\u003eBreak through single-atmosphere pollution perspectives, proceed from regional ecosystem integrity, establish linkage research frameworks connecting water cycles, soil humidity, vegetation coverage, atmospheric ammonium emissions, and haze pollution, and reconceptualize the ecological causes of haze [5,6,13].\u003c/p\u003e\n\u003ch3\u003e11.6 Ecological Root-Cause\u003c/h3\u003e\n\u003cp\u003eRelying solely on end-of-pipe emission reductions and engineering pollution control cannot fundamentally resolve the ecological substrate causes of frequent haze outbreaks; return to the ecological origin of soil-water-air balance is essential. Haze formation is controlled by two core factors\u0026mdash;atmospheric relative humidity and suspended particulate matter concentration\u0026mdash;following the natural law that \u0026ldquo;dust settles with water and flies without water\u0026rdquo;: when soil surfaces are moist, dust particles are readily adsorbed and fixed, difficult to resuspend; when surfaces become persistently dry, even light winds can generate local dust emissions, providing continuous particulate matter substrates for haze [5,6].\u003c/p\u003e \u003cp\u003eSoil possesses solid-liquid-gas three-phase loose porous structures, naturally endowed with water conservation, pollutant adsorption and fixation, groundwater replenishment, and local microclimate humidity maintenance ecological functions; tall arbor communities can enhance air humidity through transpiration, adsorb suspended dust, fix carbon and release oxygen, and prevent wind and conserve soil and water, serving as natural urban ecological purification barriers. For an extended period, domestic haze control has excessively emphasized engineering dust suppression while neglecting the core issue of declining soil humidity and atmospheric relative humidity in Beijing\u0026rsquo;s urban areas, with continuous land drying and intensified local dust generation forming a positive feedback cycle of soil drying\u0026mdash;atmospheric humidity reduction\u0026mdash;local dust resuspension\u0026mdash;frequent haze [5,6].\u003c/p\u003e \u003cp\u003eLarge-scale enclosed sewage pipeline networks and centralized WWTP construction have diverted all urban domestic sewage to distant suburban treatment, severing natural pathways for sewage local infiltration and soil replenishment, directly causing persistent declines in urban soil moisture content and water-deficient growth decline of street trees and vegetation, substantially weakening trees\u0026rsquo; humidity enhancement and dust retention ecological functions [5,6]. Root-cause solutions should draw upon traditional decentralized ecological water utilization concepts and rural dry well local absorption models, moderately optimizing centralized sewage discharge layouts, implementing partial domestic sewage local ecological absorption and tree-soil moisture nourishment; increase urban forestland and constructed wetland construction, replenish depleted groundwater, and restore soil humidity and regional atmospheric humidity balance. Through integrated water-soil-forest ecological regulation, fundamentally suppress local dust generation and improve local microclimates, constructing stable ecological substrates for long-term haze governance [5,6].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eCompeting Interests Statement:\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eSupplementary Materials\u003c/p\u003e\n\u003cp\u003eNo supplementary materials were created for this study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Author Contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePan Xiao proposed the overall research conception of this paper. Pan Xiao, Zhang Chengpeng and Pan Xianguang jointly participated in manuscript writing, academic discussion, as well as the revision and improvement of the article.All authors approved the final version for submission,\u003c/p\u003e\n\u003cp\u003eDisclaimer/Publisher\u0026rsquo;s Note\u003c/p\u003e\n\u003cp\u003eThe statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of the Research Square and/or the editor(s). The Research Square and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.\u003c/p\u003e\n\u003cp\u003eFunding :\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003eData Availability Statement:\u003c/p\u003e\n\u003cp\u003eThe data supporting this study are available from the corresponding author upon reasonable request. Official monitoring data were obtained from the Beijing Municipal Ecology and Environment Monitoring Center, Beijing Drainage Group, and the Ministry of Ecology and Environment of China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChinese Research Academy of Environmental Sciences (2019) Research Report on Causes and Control of Heavy Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas [R]. China Environmental Science, Beijing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Ecology and Environment (2002) GB 18918\u0026ndash;2002 Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant [S]. China Environmental Science, Beijing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang YS, Zhang YM, Sun YL (2014) Seasonal variations in chemical composition and source apportionment of PM₂.₅ in Beijing [J]. Chin Sci Bull 59(17):1620\u0026ndash;1629\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuan JN, Xu XD, Jia XC (2020) Multi-scale processes affecting haze weather in China [J]. Chin Sci Bull 65(9):810\u0026ndash;824\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang XY, Zhang YM, Cao GL (2016) Meteorological conditions and formation mechanisms of haze pollution in China [J]. Acta Meteorologica Sinica 74(1):1\u0026ndash;16\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuan JN, Xu XD, Jia XC (2020) Multi-scale processes affecting haze weather in China [J]. Chin Sci Bull 65(9):810\u0026ndash;824\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChinese Research Academy of Environmental Sciences (2019) Research Report on Causes and Control of Heavy Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas [R]. China Environmental Science, Beijing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng B, Zhang Q, Zhang Y et al (2021) Changes in anthropogenic emissions during COVID-19 and corresponding impacts on air quality [J], vol 8. Environmental Science \u0026amp; Technology Letters, pp 551\u0026ndash;557. 7\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan FK, He KB, Sun ZL (2019) Direct observation of sulfur-nitrogen-ammonium salts during haze and its implications [J]. Acta Sci Circum 39(7):2234\u0026ndash;2241\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu S, Sun DZ (2016) Emission characteristics and control strategies of NH₃ and trimethylamine from urban WWTPs [D]. Beijing Forestry University, Beijing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi M, Zhang Q, Zheng B et al (2025) Increasing importance of ammonia emission abatement in PM₂.₅ pollution control [J], vol 32. Environmental Science and Pollution Research, pp 4521\u0026ndash;4535. 5\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang S et al (2024) Evolution and driving mechanisms of particle acidity during heavy haze processes in Beijing [J]. Clim Environ Res 29(2):193\u0026ndash;204\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNEP (2021) Global Assessment of Ammonia Emissions and Environmental Impacts [R]. United Nations Environment Programme, Nairobi\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv WL, Zhang K, Zhi MK et al (2021) Effects and sensitivity analysis of NH₃ and liquid water content on SNA formation in PM₂.₅ in winter [J]. Res Environ Sci 34(5):1053\u0026ndash;1062\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu X, Zhang Y, Han W et al (2025) Reactive nitrogen-driven atmospheric multiphase buffering triggers concurrent pollution [J]. Nat Commun 16:1234\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang WW, Li HL, Lun ZC (2023) Fugitive emission characteristics and risk assessment of malodorous gases from A\u0026sup2;O process WWTPs [J]. Chin J Environ Eng 17(10):3342\u0026ndash;3348\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei J, Li Z, Chen X et al (2023) Separating daily 1 km PM₂.₅ inorganic chemical components in China since 2000 via deep forest learning [J], vol 57. Environmental Science \u0026amp; Technology, pp 7100\u0026ndash;7111. 18\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu S, Sun DZ (2016) Emission characteristics and control strategies of NH₃ and trimethylamine from urban WWTPs [D]. Beijing Forestry University, Beijing\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeijing Municipal Ecology and Environment Bureau (2023) Beijing Environmental Status Bulletin (2000\u0026ndash;2023) [R]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng S, Li Y, Zhang W et al (2024) Source apportionment of atmospheric ammonia in suburban Beijing revealed through \u0026sup1;⁵N-stable isotopes [J]. Sci Total Environ 912:168723\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv WL, Zhang K, Zhi MK et al (2021) Effects and sensitivity analysis of NH₃ and liquid water content on SNA formation in PM₂.₅ in winter [J]. Res Environ Sci 34(5):1053\u0026ndash;1062\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeijing Municipal Ecology and Environment Bureau (2025) Beijing Ecological Environment Status Bulletin (1996\u0026ndash;2025) [R]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeijing Drainage Group (2022) Monitoring and Technical Reform Report on Ammonia Emissions from Sludge Disposal in Municipal WWTPs [R]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChinese Research Academy of Environmental Sciences (2016) Research on atmospheric ammonia emission inventory and haze causes in Beijing-Tianjin-Hebei [J]. Acta Sci Circum 36(8):2801\u0026ndash;2808\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang TT, Wang Q (2020) Component characteristics of PM₂.₅ in Beijing and effects of ammonium salts on haze pollution [J]. Res Environ Sci 33(5):1123\u0026ndash;1130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Liu YS (2019) Atmospheric emission reduction benefits of anaerobic fermentation replacing aerobic composting for sludge treatment [J], vol 35. China Water \u0026amp; Wastewater, pp 106\u0026ndash;111. 11\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Ecology and Environment Environmental Monitoring Department (2025) National Urban Air Quality Monitoring Report (2013\u0026ndash;2025) [R]\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"haze, methodological bias, ammonium salts, ammonia, wastewater treatment plant, critical threshold, water-air synergy, secondary inorganic aerosol, PM₂.₅","lastPublishedDoi":"10.21203/rs.3.rs-9702485/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9702485/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCurrent haze causation studies exhibit significant methodological biases: utilizing annual average data from non-haze periods to analyze heavy pollution mechanisms, conflating the scientific definitions of basic emission sources and outbreak triggering factors, resulting in long-term deviation of governance from core issues. Based on the time-series data of Beijing\u0026rsquo;s wastewater treatment industry from 1954 to 2014 and the spatiotemporal distribution characteristics of haze, this study reveals through logical deduction, component correspondence, and spatiotemporal matching verification that haze is a sudden air pollution phenomenon resulting from the coupling of basic precursors, ammonium triggering factors, and extreme meteorological conditions. Research indicates that motor vehicles, coal combustion, and industrial emissions only provide conventional precursors such as SO₄\u0026sup2;⁻ and NO₃⁻; NH₃ released from municipal wastewater treatment plants (WWTPs) is the key triggering factor driving rapid secondary formation of ammonium sulfate and ammonium nitrate under stable and humid meteorological conditions, inducing nonlinear jumps in PM₂.₅ concentrations. Atmospheric NH₃ concentration of approximately 8 \u0026micro;g/m\u0026sup3; serves as a universal critical threshold for PM₂.₅ outbreaks. After Beijing upgraded sludge treatment processes from open aerobic composting to enclosed anaerobic digestion in 2014, annual average boundary NH₃ concentrations decreased from 3.0\u0026ndash;8.0 mg/m\u0026sup3; to 0.2\u0026ndash;1.2 mg/m\u0026sup3;, and heavy haze days decreased from 58 d/a to 1\u0026ndash;4 d/a, directly confirming the causal relationship between WWTP ammonia emissions and haze outbreaks. The study also reveals that frequent haze is an external manifestation of regional water cycle imbalance and soil-water ecological degradation. Correcting methodological biases, implementing water-air collaborative governance, and reconstructing decentralized ecological water utilization patterns constitute the scientific pathway to resolving the persistent dilemma of haze control.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Methodological Reconstruction of Ammonium-Salt Haze Triggering Mechanism: Critical Threshold Effect of Ammonia Emissions from Municipal Wastewater Treatment Plants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 16:09:33","doi":"10.21203/rs.3.rs-9702485/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b75c5b6c-4e16-4136-9d27-2f03a226a834","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T16:09:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 16:09:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9702485","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9702485","identity":"rs-9702485","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}