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The North China Plain is a crucial agricultural region in China, but irregular precipitation patterns have led to significant water shortages. To address this, analyzing the high-resolution dynamics of root-zone soil moisture transport is essential for optimizing irrigation strategies and improving water resource efficiency. The Richards equation is a robust model for describing soil moisture transport dynamics across multiple soil layers, yet its application at large spatial scales is hindered by its sensitivity to boundary conditions and model parameters. This study introduces a novel approach that, for the first time, employs a continuous time series of near-surface soil moisture as the upper boundary condition in the Richards equation to estimate high-resolution root-zone soil moisture in the North China Plain, thus enabling its large-scale application. Singular spectrum analysis (SSA) was first applied to reconstruct site-specific time series, filling in missing and singular values. Leveraging observational data from 617 monitoring sites across the North China Plain and multiple spatial covariates, we developed a machine learning model to estimate near-surface soil moisture at a 1 km resolution. This high-resolution, continuous near-surface soil moisture series then served as the upper boundary condition for the Richards equation, facilitating the estimation of root-zone soil moisture across the region. The results indicated that the machine learning model achieved a correlation coefficient (R) of 0.92 for estimating spatial near-surface soil moisture. Analysis of spatial covariates showed that atmospheric forcing factors, particularly temperature and evaporation, had the most substantial impact on model performance, followed by static factors such as latitude, longitude, and soil texture. With a continuous time series of near-surface soil moisture, the Richards equation method accurately predicted multi-layer soil moisture and demonstrated its applicability for large-scale spatial use. The model yielded R values of 0.97, 0.78, 0.618, and 0.43, with RMSEs of 0.024, 0.06, 0.08, and 0.11, respectively, for soil layers at depths of 10 cm, 20 cm, 40 cm, and 100 cm across the North China Plain. [ABSTRACT FROM AUTHOR]

Land use and land cover changes (LULCC) alter local surface attributes, thereby modifying energy balance and material exchanges, ultimately impacting meteorological parameters and air quality. The North China Plain (NCP) has undergone rapid urbanization in recent decades, leading to dramatic changes in land use and land cover. This study utilizes the 2020 land use and land cover data obtained from the MODIS satellite to replace the default 2001 data in the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model. It simulates and analyzes the direct impact of LULCC on meteorological parameters and the indirect impact on surface ozone (O3) concentration through physical and chemical processes in the North China Plain during July in the summer. Six rapidly urbanizing cities were selected to represent the North China Plain. The results show that LULCC significantly increased sensible heat flux and 2-m temperature in rapidly urbanizing areas throughout the diurnal cycle, with more pronounced effects during the daytime, ranging from 6.49 to 23.46 W/m2 and 0.20–0.59 °C, respectively. The 10-m wind speed decreased at night and increased during the day, with changes ranging from − 0.43 to 0.27 m/s at night and − 0.16 to 0.15 m/s during the day. The planetary boundary layer height generally increased, with a larger rise during the daytime, ranging from 23.63 to 84.74 m. Simultaneously, surface O3 concentrations increased during both daytime and nighttime. The daytime increase ranged from 2.89 to 9.82 μg/m3, while the nighttime increase ranged from 1.76 to 7.77 μg/m3. LULCC enhanced meteorological and chemical processes as well as vertical transport, leading to an increase in O3. At the same time, it reduced the increase in O3 through horizontal transport and dry deposition processes. These changes are related to the meteorological variations. The impact on O3 concentrations was not limited to the surface but extended to the top of the planetary boundary layer (approximately 1500 m). Below 500 m, vertical transport increased O3 concentrations, while horizontal transport decreased O3 concentrations. Additionally, the meteorological and chemical processes induced by LULCC showed enhanced effects above the surface, whereas the dry deposition process had a smaller impact on O3 concentrations above the surface. This study reveals the significant impact of urban expansion on regional meteorological parameters and air quality. It optimizes the model’s simulation of regional air quality and provides new insights into understanding the effects of urbanization on meteorological conditions and air quality. [ABSTRACT FROM AUTHOR]

The distribution of rural settlements is a complex outcome of human adaptation to natural conditions and socioeconomic development throughout history. Scientifically revealing the spatially varying relationships between the distribution of rural settlements and the related factors is fundamental for effective planning and management. In this study, we focus on the North China Plain to analyze the spatially varying relationships between the distribution of rural settlements and the related factors using both traditional statistical and geographically weighted regression models. Our findings reveal that both the number and the area of rural settlements at the county level are increasing from north to south and from west to east. The results of the traditional regression model suggest that total area, total population, road density, precipitation, road length, slope, longitude, and temperature significantly influence the rural settlement area, while those influencing the number of rural settlements are longitude, latitude, road length, road density, river length, and river density. Moreover, the regression coefficients are constant in the global model, while both the magnitude and the sign of the corresponding parameters in the local model are spatially varying. However, the value of the coefficients in the global model are within the range of the coefficients in the local model and most coefficients in the local model share the same sign with that the global model. Our results also reveal that the local model outperforms the global model with the same explanatory variables, indicating a smaller Akaike's information criterion (AIC) and a reduced Moran's I in model residual. Finally, this study also highlights the importance of the cautious and scientific interpretation of the varying relationships, especially when the unexpected results are obtained. [ABSTRACT FROM AUTHOR]

Groundwater withdrawal and recharge lead to changes in terrestrial hydrological loads, which in turn cause surface deformation. Based on poroelastic response and elastic loading theory, the 24 Global Positioning System (GPS) stations on the North China Plain (NCP) and the Gravity Recovery and Climate Experiment mission and its follow-on (GRACE/GRACE-FO) are first integrated to quantify the spatial–temporal changes in surface deformation and groundwater storage (GWS) during 2011–2022. The results show that the trends of GWS in the three periods of 2011–2017, 2018–2020, and 2021–2022 were − 2.56 ± 0.33 mm/yr, − 4.72 ± 1.74 mm/yr, and 11.76 ± 4.18 mm/yr, respectively. Most of the GPS stations showed a significant negative correlation between GWS and surface deformation under the elastic loading theory. In 2021, surface subsidence of more than 5 mm was experienced by 94% of the GPS stations, and 58% experienced more than 10 mm, further confirming that the South-to-North Water Diversion (SNWD) effectively replenishes groundwater resources in the NCP. The SNWD, precipitation, and human activity were the three principal factors influencing the groundwater in the NCP. SNWD effectively mitigated the continuous decrease of groundwater in the NCP. [ABSTRACT FROM AUTHOR]

In the North China Plain (NCP), the assessment of water surplus or deficit (WSD), which is calculated as precipitation minus reference evapotranspiration (ET0), holds significant implications for water resource management and agricultural irrigation decision‐making, given the region's long‐standing severe shortage of water resources. However, the magnitude, trend and climatic drivers of WSD remain poorly understood in the NCP. This study analysed the spatial and temporal characteristics of WSD, and quantified the contribution of climatic factors to WSD based on the sensitivity and contribution rate analysis methods with climatic data from 75 meteorological stations. The result showed that: (1) Annual WSD decreased mainly in northeastern NCP and increased significantly in southern NCP during 1961–2022. Annual WSD increased slightly from 1961 to 2022 at a rate of 1.63 mm a−2 mainly due to the more significant decrease (−1.88 mm a−2) in ET0 compared to precipitation (−0.25 mm a−2). (2) In terms of the sensitivity of WSD to climatic factors, relative humidity had the highest sensitivity, followed by net radiation, wind speed, precipitation and average air temperature. (3) Significant declines of wind speed were the most dominant factor affecting WSD variation in most part of NCP during most of a year, and net radiation of four stations in the western high‐elevation regions played the most important role. This study enhances comprehension of the impact of climate change on WSD in the NCP and provides a reference for improving management of agricultural water resources under NCP's evolving climatic conditions. [ABSTRACT FROM AUTHOR]

For sustainable conservation and management of wetlands, it is essential to quantify the evolution progress and driving mechanisms of wetlands. This study examined Baiyangdian Wetland as a research area, and remote images and statistical yearbooks were used as data sources. Dominant zones of wetland were defined based on spatial characteristics of land cover frequency. A transfer matrix and random forest were used to analyze the evolution process and driving mechanism of typical wetlands in the North China Plain. Based on the results, following conclusions were arrived: (1) There was significant spatial differentiation of land cover frequency characteristics in the Baiyangdian wetland, with the cultivated land-dominated zone, the aquatic vegetation-dominated zone, and the water body-dominated zone being the three core zones of wetland ecosystem evolution. (2) There was a frequent and significant change of the Baiyangdian wetland due to extreme climatic conditions. Between 1987 and 2017, the built-up land area and the water body area increased by 4.62 and 16.17 km2, respectively, while the aquatic vegetation area decreased by 20.70 km2. A combination of natural and human factors caused changes in the wetland's structure. (3) The driving mechanisms of ecosystem evolution in the Baiyangdian wetland were influenced significantly by space, time, and land cover types. Specifically, on a spatial scale, social factors were the predominant factors contributing to changes in water body and cultivated land in the cultivated land-dominant zone and the aquatic vegetation-dominant zone. In contrast, natural factors were the dominant factors leading to changes in aquatic vegetation. There was a greater contribution from social factors to the driving mechanism of changes in the water body, aquatic vegetation, and cultivated land in the water body-dominant zone than from natural factors. On a temporal scale, it was primarily influenced by natural factors in the early stages and socio-economic factors in the late stages, with the year 2002 serving as a turning point. The scale of land cover types can be seen primarily in the differences among the agricultural lands, aquatic vegetation, and water body. In particular, the Secondary Industry Out Value (SIOV) was highly sensitive to changes in the cultivated area. In addition, cumulative evaporation (EC) has been identified as the main factor responsible for the evolution of aquatic vegetation, which is closely related to the changes in water body. [ABSTRACT FROM AUTHOR]

The 6 August 2023 MW5.5 Pingyuan earthquake is the largest earthquake in the central North China Plain (NCP) over the past two decades. Due to the thick sedimentary cover, no corresponding active faults have been reported yet in the epicenter area. Thus, this earthquake presents a unique opportunity to delve into the buried active faults beneath the NCP. By integrating strong ground motion records, high-precision aftershock sequence relocation, and focal mechanism solutions, we gain insights into the seismotectonics of the Pingyuan earthquake. The aftershocks are clustered at depths ranging from 15 to 20 km and delineate a NE-SW trend, consistent with the distribution of ground motion records. A NE-SW nodal plane (226°) of the focal mechanism solutions is also derived from regional waveform inversion, suggesting that the mainshock was dominated by strike-slip motion with minor normal faulting component. Integrating regional geological data, we propose that an unrecognized fault between the NE-SW trending Gaotang and Lingxian-Yangxin faults is the seismogenic fault of this event. Based on the S-wave velocity structure beneath the NCP, this fault probably extends into the lower crust with a high angle. Considering the tectonic regime and stress state, we speculate that the interplay of shear strain between the Amurian and South China blocks and the hot upwelling magma from the subducted paleo Pacific flat slab significantly contributed to the generation of the Pingyuan earthquake. [ABSTRACT FROM AUTHOR]

This study quantified climate effects on wheat yield heterogeneity in the North China Plain from 1960 to 2020, by integrating the Agricultural Production Systems sIMulator, Optimal Parameters-based Geographical Detector model, and Ensemble Empirical Mode Decomposition model. The factors dominating yield heterogeneity varied by growth stage. For sowing to anthesis, anthesis to maturation, and the entire growth season, minimum temperature, radiation, and vapor pressure deficit has the greatest effect on yield heterogeneity. Interannual periodic oscillations govern the long-term evolution of climate effects on yield heterogeneity from 1960 to 2020. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With global climate change posing a significant threat to agricultural production, early warning systems (EWS) play an important role in mitigating the losses induced by extreme weather. However, research on the impact of EWS on farmers’ adoption of adaptive measures remains scarce. In particular, the heterogeneous effects of EWS on farmers’ adoption of active and passive measures require further examination. This study fills this gap by categorising adaptive measures into sustained and coping measures, with the former referring to actions farmers take to prepare for future potential meteorological disasters and the latter reflecting farmers’ actions to reduce losses when facing the aftermath of previous disasters. Our analysis is based on a relatively large sample of 1,219 farmers in the North China Plain. A generalised Poisson regression model and a negative binomial regression model were used to examine the determinants of farmers’ adaptation processes. We find that EWS plays a significant role in promoting active and long-term adaptation; however, its effects on passive and short-term emergency actions are insignificant. These findings indicate that the EWS is not a ‘silver bullet’ for mitigating weather risks and should be supplemented by improving the resilience of agricultural system. [ABSTRACT FROM AUTHOR]

Properly understanding the evolution mechanisms of groundwater storage anomaly (GWSA) is the basis of making effective groundwater management strategies. However, current analysis methods cannot objectively capture the spatiotemporal evolution characteristics of GWSA, which might lead to erroneous inferences of the evolution mechanisms. Here, we developed a new framework to address the challenge of spatiotemporal heterogeneity in the GWSA evolution analysis. It is achieved by integrating the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST), the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), and the Optimal Parameters‐based Geographical Detector (OPGD). In the case study of the North China Plain (NCP), the GWSA time series is divided into four stages by three trend change points in BEAST. An increasing trend of GWSA is observed at Stage IV, and the third trend change point occurs before the third seasonal change point. This distinguishes the positive feedback of anthropogenic interventions and the effects of seasonal precipitations for the first time. Moreover, the spatial distribution of GWSA in the NCP is classified into two clusters by BIRCH in each stage. The differences in GWSA trends and responses to environmental changes between Cluster‐1 and Cluster‐2 are significant. Then the driving effects of 16 factors on the evolution of GWSA are identified using OPGD, in which the contributions of topographic and aquifer characteristics are highlighted by quantitative analysis. This framework provides a novel method for examining the spatiotemporal heterogeneity of GWSA, which can be extended to analyze spatiotemporal trends in GWSA at diverse scales. Key Points: A new framework is developed to capture spatiotemporal evolution of groundwater storage anomaly (GWSA) and improve the mechanism inferenceBy decomposing GWSA's spatiotemporal heterogeneity, the framework links its evolution to the spatiotemporal variation of driving factorsThe framework distinguishes the impacts of human interventions to the recent rise of GWSA in the North China Plain from seasonal rainfall [ABSTRACT FROM AUTHOR]

Brown carbon aerosols (BrC), a subfraction of organic aerosols, significantly influence the atmospheric environment, climate and human health. The North China Plain (NCP) is a hotspot for BrC research in China, yet our understanding of the optical properties of BrC in rural regions is still very limited. In this study, we characterize the chemical components and light absorption of BrC at a rural site during winter in the NCP. The average mass concentration of PM1 is 135.1 ± 82.3 μg/m3; organics and nitrate are the main components of PM1. The absorption coefficient of BrC (babs,BrC) is 53.6 ± 45.7 Mm−1, accounting for 39.5 ± 10.2% of the total light absorption at 370 nm. Diurnal variations reveal that the babs,BrC and organics are lower in the afternoon, attributed to the evolution of planetary boundary layers. BrC is mainly emitted locally, and both the aqueous phase and the photooxidation reactions can increase babs,BrC. Notably, the babs,BrC is reduced when RH > 65%. During foggy conditions, reactions in the aqueous phase facilitate the formation of secondary components and contribute to the bleaching of BrC. This process ultimately causes a decrease in both the absorption Ångström exponent (AAE) and the mass absorption efficiency (MAE). In contrast, the babs,BrC, along with AAE and MAE, rise significantly due to substantial primary emissions. This study enhances our understanding of the light absorption of BrC in rural polluted regions of the NCP. [ABSTRACT FROM AUTHOR]

To compensate for the coarse resolution of groundwater storage (GWS) estimation by the Gravity Recovery and Climate Experiment (GRACE) satellites and make better use of available observed groundwater‐level (GWL) data in some aquifers, a ground‐based scaling factor (SF) method is proposed here to derive high‐resolution GRACE GWS estimates. Improvement is achieved by using the gridded SF derived from assimilating ground‐based GWL observations. The proposed SF method is tested on the North China Plain (NCP, ∼140,000 km2), where a dense network of observation wells and a consistently estimated specific yield (SY) data set are available, to demonstrate its effectiveness and practical applications. The sensitivities of SF‐estimated GWS accuracy to the specification of SY and the assimilation of GWL observation data are explored through four designed numerical experiments. Results show that this novel ground‐based method can reduce the impact of SY uncertainty on GWS estimates, particularly in regions with more pronounced regional GWS trends. The accuracy of SF‐estimated GWS is primarily determined by whether the assimilated wells can reflect the regionally averaged GWS trend. GWS accuracy is less dependent on the number of available wells assimilated. The estimated GWS trend (2004–2015) in NCP is −32.6 ± 1.3 mm/yr (−4.6 ± 0.2 km3/yr), with contrasting GWS trends found in the west Piedmont Plain (∼54,000 km2, with a loss of −66.8 mm/yr) and the coastal Eastern Plain (∼20,000 km2, and a gain of +7.2 mm/yr). Despite the limitations of regional and time scale dependence inherent in SF method, this study highlights the benefits of assimilating in situ observed GWL data instead of using model simulations in estimating SF to downscale GRACE GWS to the higher‐resolution that is desired by local water resources management. Key Points: A new downscaling method based on groundwater‐based scaling factor correction is proposed to improve gravity recovery and climate experiment (GRACE) groundwater storage estimatesThe proposed method can reduce the impact of specific yield uncertainty on groundwater storage (GWS) estimation due to the GWS information provided by the assimilated wells of groundwater levelThe accuracy of GWS change based on the proposed method is primarily determined by whether the assimilated wells can reflect the regional‐averaged GWS trend, less dependent on the number of available wells assimilated [ABSTRACT FROM AUTHOR]

Background: There is an urgent need to save water and decrease fertilizer application rates in agricultural areas of the North China Plain (NCP) and similar regions. Methods: Field experiments were conducted in 2017 and 2018 in the NCP to investigate the effects of border and furrow irrigation under different fertilizer application rates on the growth, yield, and water and fertilizer use efficiencies of silage corn. The experiment applied two irrigation methods, i.e., border and furrow irrigation, each with four compound fertilizer application rates: 750, 600, 450, and 300 kg/ha. Results: While the two experiment years were normal hydrological years, variation in precipitation resulted in no irrigation being applied in 2017 and 70 mm of irrigation being applied after sowing in 2018. Plants appeared to grow slightly taller and thicker with larger leaf areas, but with a 9.7% lower fresh weight yield in 2017 relative to 2018. The actual evapotranspiration (ETa) in 2017 was 37.22 mm more than that in 2018, and the higher fresh weight yield and lower ETa caused higher water use efficiency (WUE) in 2018, which was 32% higher than that in 2017. Furrow irrigation promoted growth compared with border irrigation under the same irrigation amount, but without significant effects on fresh weight yield, ETa, or WUE of silage corn. The fertilizer application amount had a significant effect on fresh weight yield and the partial fertilizer productivity of N, P and K of silage corn, but did not affect ETa or WUE of silage corn. Additionally, the fertilizer rate of 600 kg/ha induced slightly higher growth indexes and fresh weight yields compared with the fertilizer rates of 750, 450, and 300 kg/ha. Discussion: In the NCP, lower irrigation amounts at the crop development period of silage corn appeared to promote higher yield, WUE, and fertilizer use efficiency, under the condition that there was sufficient water to ensure the emergence of seedlings. The current fertilizer application model, compound fertilizer applied with a seeder at planting, does not match the fertilizer needs of silage corn, and more efficient water and fertilizer application techniques should thus be adopted. [ABSTRACT FROM AUTHOR]

Surface ozone (O3) pollution has adverse impacts on the yield of winter wheat. The North China Plain (NCP), one of the globally significant primary regions for winter wheat production, has been frequently plagued by severe O3 pollution in recent years. In this study, the effects of O3 pollution on winter wheat yield and economic impact were evaluated in the NCP during the 2015–2018 seasons using the regional atmospheric chemical transport model (WRF-Chem), O3 metrics including the phytotoxic surface O3 dose above 12 nmol m−2 s−1 (POD12), and the accumulated daytime O3 above 40 ppb (AOT40). Results showed that the modeled O3, exposure-based AOT40, and flux-based POD12 increased during the winter wheat growing season from 2015 to 2018. The annual average daytime O3, exposure-based AOT40, and flux-based POD12 were 44 ppb, 5.32 ppm h, and 1.78 mmol m−2, respectively. During 2015–2018, winter wheat relative production loss averaged 10.9% with AOT40 and 14.6% with POD12. This resulted in an average annual production loss of 12.4 million metric tons, valued at approximately USD 4.5 billion. This study enhances our understanding of the spatial sensitivity of winter wheat to O3 impacts, and suggests that controlling O3 pollution during the key growth stages of winter wheat or improving its O3 tolerance will enhance food security. [ABSTRACT FROM AUTHOR]

It is essential to map the cropping patterns when investigating the mechanisms and impacts of climate change. However, the long-term evolution of cropping patterns remains poorly understood. This study collected hundreds of records of cropping intensity and crop combinations from local gazetteers and other relevant articles for the North China Plain (NCP) over the past 300 years. Then, we analyzed the evolutionary characteristics and drivers in terms of climate change and advances in agricultural technology. From the Qing Dynasty to the 1950s, one harvest per year (1H1Y) was the dominant pattern in the northern NCP, and three harvests in two years (3H2Y) was the dominant pattern in Henan and Shandong provinces. The 1H1Y crops were cereals and sorghum. The 3H2Y crop combinations were spring maize, winter wheat, and beans. In the 1960s and 1970s, the cropping intensity in much of the NCP was two harvests per year (2H1Y) or a mix of the 2H1Y and 3H2Y patterns. In the 1980s, the cropping intensity in the NCP was dominated by 2H1Y. Since the 1960s, the 2H1Y crop compositions have been winter wheat–summer maize in Shandong, Henan, and Hebei provinces, while winter wheat–rice dominated north of the Huaihe River. The 3H2Y summer crop changed from beans to maize/cereals over time. Climate warming was not the dominant factor driving the evolution of cropping intensity in the NCP. Advances in agricultural production conditions and reforms in production relations have promoted the rapid development of multiple cropping since the 1950s. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agro-Environment Science is the property of Journal of Agro-Environment Science Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers new insights into the causes of ground fissures in the northern North China Plain, providing crucial scientific evidence for sustaining both the natural environment and the socio-economic stability of the region. [ABSTRACT FROM AUTHOR]

Due to the overexploitation of deep groundwater, the largest cone of depression in the world has formed in the North China Plain. This led to severe geological hazards, including land subsidence and ground fissures, and also caused economic losses. The prevention and treatment of subsidence needs to rely on the accurate prediction of subsidence amount. According to the one‐dimensional consolidation theory and effective stress principle, combined with stratum structure, groundwater flow, stress distribution, and so forth, the high‐pressure consolidation test results of 569.6 m deep borehole soil samples are adopted; with a specific focus on stress and deformation parameters under exploitation of groundwater condition, the soil‐water coupling prediction model of groundwater level lowering depth and land subsidence has been established. Verification with measured subsidence data near the study sites demonstrated that the predicted curve is consistent with the measured one and the differences between them are acceptable. The model can be applied in different areas after making adjustment based on different regional stratigraphic structures. Its key advantage lies in the ability to provide land subsidence prediction for areas lacking monitoring data, making it highly valuable for widespread application. Practitioner Points: There is a compressible stratum structure; it is the internal factors of land subsidence.The groundwater level decline causes the soil body stress to change. It is land subsidence of the external factors.Based on the one‐dimensional consolidation theory and by combining stratigraphic structures, groundwater flow, and stress distribution, a ground settlement prediction model was established. [ABSTRACT FROM AUTHOR]

Exploring the coordination of agricultural water resources (W), cultivated land (L), and the ecoenvironment (E) system is crucial for sustainable agriculture in the North China Plain (NCP). However, the synergistic effects of this composite system remain unclear. Coupling coordination degrees (CCDs) of 53 cities in the NCP for the years 2011, 2015, and 2020 were evaluated using the TOPSIS model, and the coupling coordination model, combined with the analytic hierarchy process and entropy weight method. The evaluation results were further analyzed to identify obstacle factors. The findings reveal the following: (1) The comprehensive development level showed a fluctuating upward trend, with closeness values ranging from 0.418 to 0.574 in 2020, indicating an improvement of 14.6–52.3% compared to 2011. The coefficient of variation (CV) for each province rose from 12.65% in 2011 to 13.64% and subsequently declined to 9.12% by 2020. (2) Between 2011 and 2020, CCDs of the W–L–E composite system exhibited a consistent upward trend. In 2020, regions with intermediate or better coordination accounted for 34.0%, and were primarily located in Jiangsu Province, the southern part of Anhui Province, the northwestern part of Shandong Province, and the municipalities of Beijing and Tianjin. (3) In 2011 and 2015, significant obstacle factors included the water quality compliance rate and the per capita disposable income of rural residents, although these were not primary obstacles in 2020. The water supply modulus and multiple cropping index were major obstacle factors in 2011, 2015, and 2020. Developing water-appropriate cropping patterns based on regional water resource endowment is the essential path for the sustainable and coordinated development of water, land, and ecology in the NCP. [ABSTRACT FROM AUTHOR]

The effective allocation of labor and cultivated land resources to ensure food security is a global concern. Understanding the relationship between rural labor off-farm employment and the eco-efficiency of cultivated land use (ECLU) is critical, yet current research in this area remains insufficient. This study explores the dynamics between off-farm employment and ECLU using the North China Plain as a case study, analyzing panel data from 2001 to 2020 through spatial econometric models. The findings reveal significant temporal expansion and spatial differentiation in off-farm employment, with growth rates gradually slowing and spatial disparities diminishing. The average ECLU initially declined from 2001 to 2003, followed by fluctuating increases, with a notable acceleration in growth after 2017. A "U-shaped" relationship between off-farm employment and ECLU was identified, with a turning point at an off-farm employment ratio of 40.73%, occurring around 2003–2004 based on regional averages. Before this threshold, off-farm employment negatively impacted ECLU, while beyond this point, the impact became positive. The study also observed significant spatial spillover effects of off-farm employment on ECLU in the North China Plain. These findings underscore the complex interplay between rural labor migration and agricultural productivity. To maximize the benefits of off-farm employment, policies should encourage the reinvestment of income into sustainable agricultural practices. Furthermore, the significant spatial spillover effects call for enhanced regional coordination and tailored policy interventions to optimize labor allocation and improve ECLU. [ABSTRACT FROM AUTHOR]

Environmental context: Atmospheric particulate NH4+, primarily produced from the reaction of NH3 and acids, is an important component of PM2.5. In this study, nitrogen stable isotope analyses and an atmospheric chemistry model were used to estimate the contribution of major NH3 sources to particulate NH4+ in Tianjin, a megacity in North China Plain (NCP). Our research has implications for investigations of NH3 emission sources and relevant pollution control in Tianjin and NCP. Rationale: The North China Plain (NCP) has been identified as an NH3 emission hotspot. Source apportionment of NH3 is a prerequisite for controlling NH3 or NH4+ pollution. Nitrogen stable isotope (δ 15N) analysis is a promising method for NH3 source apportionment but its accuracy is still in question. Methodology: In this study, daytime and nighttime PM2.5 samples were collected from two sites in Tianjin, NCP, in autumn. Concentrations and δ 15N of particulate NH4+ were then measured. Nitrogen stable isotope analyses and isotope mixing model (MixSIAR), and an atmospheric chemistry model (WRF-CMAQ-ISAM) were used to estimate the sources of NH3 in Tianjin. Results: Results from the MixSIAR and WRF-CMAQ-ISAM models suggested that all the sources including livestock breeding, N-fertiliser application, fossil fuels, NH3 slip (especially from traffic), human waste and biomass burning (mostly from bioapplication) were non-negligible to NH3 and NH4+ in Tianjin. This high complexity is due to significant agricultural and industrial production and residential life in Tianjin and the surrounding regions. Our results indicate all NH3 sources need to be considered if we want to reduce NH4+ pollution in Tianjin in autumn. Environmental context. Atmospheric particulate NH4+, primarily produced from the reaction of NH3 and acids, is an important component of PM2.5. In this study, nitrogen stable isotope analyses and an atmospheric chemistry model were used to estimate the contribution of major NH3 sources to particulate NH4+ in Tianjin, a megacity in North China Plain (NCP). Our research has implications for investigations of NH3 emission sources and relevant pollution control in Tianjin and NCP. Photograph by Libin Wu. This article belongs to the collection Dedication to Roy Harrison. [ABSTRACT FROM AUTHOR]

Groundwater nitrate (NO3−) contamination is a global concern. The distribution patterns, enrichment mechanisms, and human health risks of NO3− contaminated groundwater were investigated using 144 groundwater samples collected from domestic and irrigation wells in the piedmonts of the North China Plain (Beijing and Shijiazhuang areas). The results showed that the groundwater was neutral to weakly alkaline, and 47% of the groundwater samples had NO3− concentrations exceeding 50 mg/L, a threshold proposed by world health organization to threaten infants up to 3 months. Groundwater NO3− concentrations were generally higher in the Beijing piedmont than in the Shijiazhuang piedmont and decreased with depth in both piedmonts. High-NO3− (> 50 mg/L) groundwater was distributed sporadically spatially and mainly was of Ca–Mg–HCO3 hydrochemical facies. Stable isotopes (D and 18O) compositions and NO3−/Cl− ratios indicated that NO3− accumulation in groundwater was primarily due to use of N-fertilizers under agricultural practices, and was associated with groundwater recharge sources such as septic tank leakage and re-infiltration of reclaimed irrigation water. Water quality evaluation showed that groundwater quality was highly dependent on NO3− concentration, with entropy-weighted water quality index values increasing linearly with increasing NO3− concentrations. The potential health risk of high-NO3− groundwater was the most serious for infants in both the piedmonts. Therefore, reducing NO3− input from sources and drinking water intake is recommended to minimize the human health risk. [ABSTRACT FROM AUTHOR]

The distribution of rural settlements is a complex outcome of human adaptation to natural conditions and socioeconomic development throughout history. Scientifically revealing the spatially varying relationships between the distribution of rural settlements and the related factors is fundamental for effective planning and management. In this study, we focus on the North China Plain to analyze the spatially varying relationships between the distribution of rural settlements and the related factors using both traditional statistical and geographically weighted regression models. Our findings reveal that both the number and the area of rural settlements at the county level are increasing from north to south and from west to east. The results of the traditional regression model suggest that total area, total population, road density, precipitation, road length, slope, longitude, and temperature significantly influence the rural settlement area, while those influencing the number of rural settlements are longitude, latitude, road length, road density, river length, and river density. Moreover, the regression coefficients are constant in the global model, while both the magnitude and the sign of the corresponding parameters in the local model are spatially varying. However, the value of the coefficients in the global model are within the range of the coefficients in the local model and most coefficients in the local model share the same sign with that the global model. Our results also reveal that the local model outperforms the global model with the same explanatory variables, indicating a smaller Akaike’s information criterion (AIC) and a reduced Moran’s I in model residual. Finally, this study also highlights the importance of the cautious and scientific interpretation of the varying relationships, especially when the unexpected results are obtained.

The development of earth fissures in a certain area often has certain genetic correlations, which is called ‘group-developing phenomenon’ of earth fissures. So far, 41 earth fissures have developed in the Beijing area in the North China Plain. Surveys and exploration studies have shown that these earth fissures have a good correspondence relationship with the activities of the adjacent control faults. Accordingly, they can be divided into 9 zones. The mechanical analysis of these fissures groups reveals that they are roughly formed through 3 models, namely, ‘contemporaneous model’ (dip-slipping movement), ‘secondary model’ (strike-slipping movement) and ‘companion model’ (basin extension movement). The characteristics of this type (fault-controlled) earth fissures in combination with their distribution regularities in the area can be used to indicate that the distribution of subsurface tectonic stress fields is as a whole an extension of the NW-SE-trending, which is not completely consistent with the near E-W-trending extension of deep material migration. These analyses show that under the background of extensional deformation of the basin, the subsurface stress field characteristics of superficial formations are more complex, which not only embodies the movement form (unity) of the deep structure in whole, but also partially reflects the adjustability of the regional tectonic stress field.

Abstract Traditional decomposition integration models decompose the original sequence into subsequences, which are then proportionally divided into training and testing periods for modeling. Decomposition may cause data aliasing, then the decomposed training period may contain part of the test period data. A more effective method of sample construction is sought in order to accurately validate the model prediction accuracy. Semi-stepwise decomposition (SSD), full stepwise decomposition (FSD), single model semi-stepwise decomposition (SMSSD), and single model full stepwise decomposition (SMFSD) techniques were used to create the samples. This study integrates Variational Mode Decomposition (VMD), African Vulture Optimization Algorithm (AVOA), and Least Squares Support Vector Machine (LSSVM) to construct a coupled rainfall prediction model. The influence of different VMD parameters α is examined, and the most suitable stepwise decomposition machine learning coupled model algorithm for various stations in the North China Plain is selected. The results reveal that SMFSD is relatively the most suitable tool for monthly precipitation forecasting in the North China Plain. Among the predictions for the five stations, the best overall performance is observed at Huairou Station (RMSE of 18.37 mm, NSE of 0.86, MRE of 107.2%) and Jingxian Station (RMSE of 24.74 mm, NSE of 0.86, MRE of 51.71%), while Hekou Station exhibits the poorest performance (RMSE of 25.11 mm, NSE of 0.75, MRE of 173.75%).

Long-term mapping of winter wheat is vital for assessing food security and formulating agricultural policies. Landsat data are the only available source for long-term winter wheat mapping in the North China Plain due to the fragmented landscape in this area. Although various methods, such as index-based methods, curve similarity-based methods and machine learning-based methods, have been developed for winter wheat mapping based on remote sensing, the former two often require satellite data with high temporal resolution, which are unsuitable for Landsat data with sparse time-series. Machine learning is an effective method for crop classification using Landsat data. Yet, applying machine learning for winter wheat mapping in the North China Plain encounters two main issues: 1) the lack of adequate and accurate samples for classifier training; and 2) the difficulty of training a single classifier to accomplish the large-scale crop mapping due to the high spatial heterogeneity in this area. To address these two issues, we first designed a sample selection rule to build a large sample set based on several existing crop maps derived from recent Sentinel data, with specific consideration of the confusion error between winter wheat and winter rapeseed in the available crop maps. Then, we developed an optimal zoning method based on the quadtree region splitting algorithm with classification feature consistency criterion, which divided the study area into six subzones with uniform classification features. For each subzone, a specific random forest classifier was trained and used to generate annual winter wheat maps from 2013 to 2022 using Landsat 8 OLI data. Field sample validation confirmed the high accuracy of the produced maps, with an average overall accuracy of 91.1% and an average kappa coefficient of 0.810 across different years. The derived winter wheat area also has a good correlation (R2 = 0.949) with census area at the provincial level. The results underscore the reliability of the produced annual winter wheat maps. Additional experiments demonstrate that our proposed optimal zoning method outperforms other zoning methods, including Köppen climate zoning, wheat planting zoning and non-zoning methods, in enhancing wheat mapping accuracy. It indicates that the proposed zoning is capable of generating more reasonable subzones for large-scale crop mapping.

Winter wheat–summer maize cropping system in the North China Plain often experiences drought-induced yield reduction in the wheat season and rainwater and nitrogen (N) fertilizer losses in the maize season. This study aimed to identify an optimal interseasonal water- and N-management strategy to alleviate these losses. Four ratios of allocation of 360 kg N ha−1 between the wheat and maize seasons under one-time presowing root-zone irrigation (W0) and additional jointing and anthesis irrigation (W2) in wheat and one irrigation after maize sowing were set as follows: N1 (120:240), N2 (180:180), N3 (240:120) and N4 (300:60). The results showed that under W0, the N3 treatment produced the highest annual yield, crop water productivity (WPC), and nitrogen partial factor productivity (PFPN). Increased N allocation in wheat under W0 improved wheat yield without affecting maize yield, as surplus nitrate after wheat harvest was retained in the topsoil layers and available for the subsequent maize. Under W2, annual yield was largest in the N2 treatment. The risk of nitrate leaching increased in W2 when N application rate in wheat exceeded that of the N2 treatment, especially in the wet year. Compared to W2N2, the W0N3 maintained 95.2% grain yield over two years. The WPC was higher in the W0 treatment than in the W2 treatment. Therefore, following limited total N rate, an appropriate fertilizer N transfer from maize to wheat season had the potential of a “triple win” for high annual yield, WPC and PFPN in a water-limited wheat–maize cropping system.

The North China Plain (NCP) serves as the main grain production land in China, functioning as a critical region for ensuring China's food security. To address the multifaceted challenges confronting food security in the NCP, the study embarked on a comprehensive analysis of the synergistic interactions between agricultural water usage, carbon emissions, and ecosystem health. By proposing footprint family indicators and using the bottom-up IPCC coefficient approach, this study quantitatively evaluates the spatial–temporal changes of water–carbon–ecological footprints in NCP from 2003 to 2020. Furthermore, a coupling coordination degree model that focuses on the coordination of water–carbon–ecological footprints is established. The findings are as follows: (1) The total water footprint in the NCP showed a striking increasing trend with an increase of 1.52 × 1011 m3, and the carbon footprint increased by 1.27 × 109 t, with significant ecological impacts. (2) The NCP's ecological footprint exhibited an "M"-shaped trend. The land structure maintained stable with negligible changes in the proportion of ecological footprints. (3) The coupling degree between the footprints of water, carbon, and ecology in the NCP is high, revealing a noteworthy interaction effect. This research can provide data support for effective resources allocation and sustainable social–economic development, offering reasonable insights for China to formulate more scientific policies of green transition in land use and ecological civilization construction. [ABSTRACT FROM AUTHOR]

[Background] Soil salinization is one of the greatest global challenges that seriously affects agricultural productivity and environmental sustainability, the severity of soil salinization is reportedly increasing in China, India, Pakistan, Australia, China, Middle Eastern countries and the US. The depth of shallow groundwater has an important influence on land salinization, and in the past, groundwater in North China Plain was constantly used for irrigation, leading to a continuous decline in the groundwater level. In recent years, both deep and shallow groundwater levels in North China Plain have risen as a result of the ban on excessive use of groundwater in North China Plain and the implementation of the South-to-North Water Diversion Project. Under the new situation of the rising groundwater level in North China Plain, how the characteristics of water and salt transport in the farmland of North China Plain will change, and its response mechanism to the depth of groundwater burial needs to be further explored. Shallow groundwater affects crop growth and yield by altering the moisture and salinity of the soil profile in agricultural fields, and the process is complicated by its hydro-chemical changes. [Objective] In order to study the distribution pattern of soil water salinity content and its effect on crop yield at different shallow groundwater burial depths, as well as the changes in groundwater chemistry. [Method] Relying on the volumetric evapotranspiration meter sample site, four groundwater depth treatments were set up, namely G0 (no groundwater burial depth), G1 (groundwater burial depth of 40 cm), G2 (groundwater burial depth of 70 cm), G3 (groundwater burial depth of 110 cm) and G4 (groundwater burial depth of 200 cm), and G4 (groundwater burial depth of 150 cm), using weekly as the monitoring frequency, to monitor changes in the content of various ions in shallow groundwater and changes in moisture and salinity in the soil of summer maize fields under evapotranspiration conditions. [Result] (1) The deeper the groundwater burial depth, the lower the water content and salinity of the surface layer (0-20 cm) soil. Compared with G0, the water content of surface soil in G1 and G2 increased significantly by 27.54% and 26.97%, respectively, and G3 increased by 8.25%, while G4 increased by only 2.18%; Surface soil salinity increased by 0.79, 0.47, and 0.43 g/kg in G1, G2, and G3 treatments, respectively, while it decreased by 0.01 g/kg in G4 treatment. Among them, salts in G1, G2 and G3 treatments mainly accumulated in the soil surface layer, while G4 treatment mainly accumulated in the 40*70 cm soil layer;(2) There was a linear relationship between groundwater depth and surface (0-20 cm) soil water content and salinity, with surface soil water content decreasing by 0.53% and salinity decreasing by 0.065 g/kg for every 0.1 m increase in groundwater depth. (3) The main cations in shallow groundwater are Na+ and Mg2+, and the main anions are SO4 2- and HCO3-. Concentrated rainfall can change the ion type in shallow groundwater from Na-Cl-SO4 to Na-HCO3; (4) Under strong surface evaporation, the ion concentration in water rised faster the shallower the depth of groundwater table. Among them, HCO3- concentration fluctuated greatly in each treatment, with a general upward trend; while NO3-, due to the effect of fertilizer application, the shallower the depth of groundwater burial the faster NO3- peaked in the shallow groundwater and the higher the concentration. [Conclusion] In this study, increasing the depth of shallow groundwater to 1.5 m can effectively reduce the water-salt content of the surface soil, reduce the influence of shallow groundwater by evaporation, precipitation, and other climatic conditions. A shallow groundwater depth of 1.2 m was optimal for summer maize growth and yield. The study of the effects of different shallow groundwater burial depths on soil moisture and salinity in agricultural soils helps to understand the migration of water and salt in agro-ecosystems and the mechanism of groundwater-soil interaction, which is of great importance for preventing soil salinization and safeguarding crop yields. [ABSTRACT FROM AUTHOR]

The North China Plain is the core region of China's economic development, and exploring the impacts of its land use and cover change (LUCC) and different urbanization regional drivers on carbon stocks is conducive to promoting sustainable development and carbon balance within the region. In the study, the North China Plain was selected as the study area, and the Patch-Generating Land Use Simulation (PLUS) model and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were comprehensively applied to set up three land use policies, predict land use changes in 2030, and calculate carbon stock changes. Meanwhile, the Extreme Gradient Boosting (XGBoost) algorithm was used to analyze the degree of influence of different drivers on the supply of carbon stocks in different urbanization regions. Studies show that if the North China Plain prioritizes economic development, the area of farmland and forests will significantly decrease, leading to a substantial decline in carbon stocks. If ecological protection is the development focus, the reduction in farmland and forests will be less, and carbon stocks will remain relatively stable. If farmland protection is the development focus, the reduction in farmland will be minimal, but there will still be some impact on carbon stocks. The driving forces of carbon stock supply vary significantly across different regions. In underdeveloped regions, population density and vegetation cover have a greater impact on carbon stocks. In developing and urban–rural combined regions, vegetation cover and population migration have a greater impact on carbon stocks. In developed regions, the area of artificial land and gross domestic product (GDP) have a greater impact on carbon stocks. The study results provide scientific evidence for regional land use planning and policy formulation. [ABSTRACT FROM AUTHOR]

Groundwater storage anomaly (GWSA) can be estimated either at the large scale from the Gravity Recovery and Climate Experiment (GRACE) or at the local scale based on in situ observed groundwater level (GWL) and aquifer storage parameters. Yet, the accuracy of GRACE‐based estimate is affected by leakage errors, while that of local GWL‐based estimate requires the reliable specific yield (Sy) data that are usually not available. Here, we developed a novel approach, the coordinated forward modeling (CoFM), based on the iterative forward modeling to improve GWSA estimation at the sub‐regional scale smaller than the typical GRACE footprint. It is achieved by solving Sy through iterative comparisons between GRACE‐based and observation‐based GWSA at 0.5° grid scale, and then re‐calculating GWSA using the updated Sy and observed GWL. The utility of CoFM is explored by using the hypothetical experiments and a real case study in the Piedmont Plain (PP, ∼54,000 km2) and East‐central Plain (ECP, ∼86,000 km2) of North China Plain. Results show that CoFM can detect GWSA at 0.5° grid scale in the hypothetical experiments given the large spatial variability of GWL. While in the real case study, the CoFM distinguishes between the divergent unconfined GWSA trends (2005–2016) in PP (−41.80 ± 0.55 mm/yr) and ECP (−7.57 ± 0.60 mm/yr) caused by the differences in hydrogeological conditions and groundwater use. The improvement made by CoFM can be attributed to the use of the distributed GWL information to constrain GRACE leakage errors. This study highlights a practical important solution for improving sub‐regional GWSA estimation through the joint use of large‐scale GRACE data and local‐scale well observations. Key Points: A coordinated forward modeling (CoFM) is developed to utilize in situ groundwater level to constrain Gravity Recovery and Climate Experiment leakage errorsCoFM enables the estimation of sub‐regional groundwater storage variations without requiring reliable specific yield dataCoFM estimates groundwater depletion rate in the piedmont unconfined aquifers of North China Plain (NCP) is ∼6 times of that in the east‐central area of NCP [ABSTRACT FROM AUTHOR]

In order to better understand the migration characteristics of ciprofloxacin (CIP) in specific types of soils, two soil samples with significant organic matter composition and physical and chemical properties potentially influenced by different geological and environmental backgrounds were selected from the groundwater irrigated farmland area of the North China Plain, and the adsorption-desorption mechanism of CIP in soil was studied kinetically and thermodynamically. The findings show that the kinetic experimental data are more in line with the quasi-second-order kinetic equation and the isothermal models are nonlinear, of which the Langmuir model turns out the best fitting. The parameters of adsorption kinetics constant (K2, 8 772.64 vs 2 846.37 g/(mg·h)), adsorption equilibrium rate constant (K1, 0.113 vs 0.094 L/mol) and maximum adsorption capacity (Qm, 5 033 vs 3 167 mg/kg) altogether exhibited higher values for Xianxian samples than those for the Zhengding, indicating faster adsorption rate and greater adsorption capacity of Xianxian soil. Correspondingly, the desorption rate (5.98% vs 8.07%), the maximum desorption amount (6 592 vs 7 564 mg/kg) and the adsorption free energy ΔG (-25.08 vs -23.00 kJ/mol) obtained from the desorption experiment consistently reflected that the soil in Xianxian County had better adsorption performance for CIP than the soil in Zhengding County. Based on the results of comprehensive experimental research and the analysis of spectral characteristics and physicochemical parameters, it is concluded that the high molecular weight, high aromaticity and multi-functional humus components of Xianxian soil and higher clay content are important factors for its overall better adsorption effect. The physical adsorption mechanism such as hydrophobic effect and electrostatic effect of humus molecules may play more active role in the adsorption of CIP antibiotics in Xianxian soil. [ABSTRACT FROM AUTHOR]

Over the past decade, surface ozone has emerged as a significant air pollutant in China, especially in the North China Plain (NCP). For effective ozone management in the NCP, it is crucial to accurately estimate the surface ozone levels and identify the primary influencing factors for ozone pollution in this region. This study utilized ozone precursors such as volatile organic compounds (VOCs) and nitrogen oxides (NOX), meteorological data, land cover, normalized difference vegetation index (NDVI), terrain, and population data to build an extreme gradient boosting (XGBoost)-based ozone estimation model in the NCP during 2019 to 2021. Four ozone estimation models were developed using different NO2 and formaldehyde (HCHO) datasets from the Sentinel-5 TROPOMI observations and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data. Site-based validation results of these four models showed high accuracy with R2 values above 0.86. Among these four models, two models with higher accuracy and higher spatial coverage ratio were selected, and their results were averaged to produce the final ozone estimation products. The results indicated that VOCs and NOX were the two main pollutants causing ozone pollution in the NCP, and their relative contributions accounted for more than 23.34% and 10.23%, respectively, while HCHO also played a significant role, contributing over 5.64%. Additionally, meteorological factors also had a notable impact, contributing 28.63% to ozone pollution, with each individual factor contributing more than 2.38%. The spatial distribution of ozone pollution identified the Hebei–Shandong–Henan junction as a pollution hotspot, with the peak occurring in summer, particularly in June. Therefore, for this hotspot region in the NCP, promoting the reduction in VOCs and NOx can play an important role in the mitigation of O3 pollution and the improvement in air quality in this region. [ABSTRACT FROM AUTHOR]