In order to improve the accuracy and credibility of the assessment of water environment and the traceability of pollution, based on the data from six routine monitoring sections of Mulan River from 2015 to 2019, the Monte Carlo simulation method was used to calculate the comprehensive pollution index (H). The influencing factors of the comprehensive pollution index were identified through correlation and sensitivity analysis. Finally, the positive matrix factor model (PMF) was used to trace the pollution. The results showed that: ① From 2015 to 2019, the H value in the study area was 0.67-0.81, and the water quality showed an overall improvement trend except for slight fluctuations in 2017 and 2018. There was a significant deterioration from upstream to downstream, with partial improvement in P4 section and P5 section in the middle reaches, which were influenced by land use types. ② Correlation analysis showed that P3 section in upstream had the greatest impact on the regional H value in 2015 and 2018, when pollution levels were severe, while P6 section in downstream had the greatest impact on the regional H value in 2016, 2017, and 2019, when pollution levels were relatively low. Sensitivity analysis showed that TN was the main influencing indicator of the comprehensive pollution index in the studied area. ③ PMF traceability results indicated that the order of contribution rates of pollution sources in the studied area during flood season were agricultural pollution (33.5%) > domestic sewage and industrial wastewater (31.0%) > organic pollution sources (21.2%) > seasonal effects (14.3%), and the order of contribution rates of pollution sources during non-flood season were agricultural pollution (25.0%) > domestic sewage (22.0%) > seasonal effects (20.3%) > organic pollution sources (18.1%) > industrial point sources (14.6%).

To elucidate the spatial variation patterns and influencing mechanisms of soil organic carbon density, the Bohai Rim region was selected as the studied area. Based on the soil datasets of SoilGrids250 m, HWSD, WISE30sec and GSDE, ArcGIS technology was used to analyze the spatial distribution characteristics of soil organic carbon density and storage. The effects of soil physicochemical properties, climate, and topographic factors on soil organic carbon density were explored through correlation analysis and random forest methods. The results showed that: ① In the Bohai Rim region, soil organic carbon density gradually increased from the southwest to the northeast at depths of [0, 30] cm, (30, 100] cm, and (100, 200]cm; ② There was spatial heterogeneity in soil organic carbon density estimated from the four datasets, mainly manifested in the eastern part of Liaoning Province and the northern part of Hebei Province. ③ There were differences in soil organic carbon storage under different land use types. The soil organic carbon storage in dry land was the highest, followed by forest land, grassland, and urban and rural land. ④ Total nitrogen, temperature, precipitation and normalized difference vegetation index were the main factors influencing soil organic carbon density.

To investigate the pollution characteristics, health risks, and sources of radioactive nuclides uranium (U) and thorium (Th) in Beidagang Reservoir, their concentrations in the water were determined using solid-phase extraction coupled with inductively coupled plasma mass spectrometry (ICP-MS). The pollution level and health risks posed by U and Th were assessed via the Nemerow composite pollution index method and health risk models, incorporating Monte-Carlo simulations. Finally, pollution source apportionment was conducted using the positive matrix factorization (PMF) model. The results showed that: ① The activity concentrations of U and Th in the water of Beidagang Reservoir were (50.5 ± 16.5) mBq/L and (0.074 ± 0.034) mBq/L, respectively. Concentrations during the dry season were higher than those in the wet season, primarily due to reduced precipitation recharge and enhanced evaporation. ② During the wet season, the probabilities of the water being at clean and relatively clean levels were 3.16% and 96.80%, respectively, with a 0.04% probability of slight pollution. In the dry season, the probability of the water being at clean and relatively clean levels were 0% and 83.50%, while the probabilities of slight and moderate pollution were 16.14% and 0.36%, respectively. ③ The total carcinogenic risk index of U and Th was 13.93 × 10^-6, indicating a potential carcinogenic risk. The chemical toxicity hazard quotient was minimal, suggesting that chemical toxicity could be neglected. ④ The pollution source analysis results showed that the main sources of radioactive nuclide U in Beidagang Reservoir were soil, agriculture, marine, and industrial, with contribution rates of 24.6%, 50.8%, 20.9%, and 3.7%, respectively. The main sources of Th were soil, marine, and industrial, with contribution rates of 57.6%, 32.6%, and 9.8%, respectively.

In order to obtain the spatial distribution of crops in Yutian County, explore the distribution laws of crops, and visualize the distribution of crop structures, the areas of major crops in Yutian County were extracted, and a thematic atlas was formed and visualized using remote sensing images and combining supervised classification with crop phenological periods. The results show that the crop extraction effect is good, and the area accuracy reaches 88%; the color matching of the thematic atlas is a combination of cold and warm tones, which overall has a certain sense of balance. The thematic map design aims to present the crop planting structure of Yutian County to the public, focus on the visualization of crop spatial distribution, and reflect the agricultural planting characteristics of Yutian County. The proposed methods and design concepts can provide not only method references and idea references for the design of similar types of atlases, but also literature materials for related scientific research and public science popularization education.