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The objective of this study was to explore the effects of different amounts of biochar on the migration process and characteristics of NO 3 - -N in loessial soil. In this study, six groups of mixed soil samples with biochar and loessial soil mass ratios of 0% (T0), 1% (T1), 2% (T2), 3% (T3), 4% (T4), and 5% (T5) were used as research objects. NO 3 - -N was used as the tracer. Through the indoor soil column solute transport simulation tests, the effects of different biochar application amounts on the NO 3 - -N transport process in loessial soil were simulated and studied. The results showed that the breakthrough curve of NO 3 - -N in loessial soil shifted to the right with the increasing of biochar application, and the peak value gradually decreased. The initial penetration time, complete penetration time, and total penetration time increased with the increasing of biochar application amount. The total penetration time of NO 3 - in the T1, T2, T3, T4, and T5 treatments was 1.26, 2.31, 2.72, 3.22, and 3.57 times that of T0, respectively. The R 2 was > 0.997 and RMSE was < 2.083 of the two-zone model (TRM). Compared with the convection-dispersion equation (CDE), the TRM model had higher fitting accuracy and could better simulate the NO 3 - -N migration process in loessial soil after the application of different contents of biochar. The analysis of the fitting parameters of the TRM model showed that the average pore velocity, hydrodynamic dispersion coefficient, and water content ratio in the movable zone gradually decreased with the increasing of biochar application, whereas the dispersion and mass exchange coefficient showed an increasing trend. The results showed that biochar application could effectively enhance the ability of loessial soil to fix NO 3 - -N, reduce the leakage of NO 3 - -N to groundwater, and play an important role in maintaining soil fertility and preventing groundwater pollution.

In order to ascertain the distribution characteristics of soil heavy metal pollution and main pollution sources in a small watershed in the southern mountainous area of Ningxia and to ensure the quality of the soil environment, the contents of heavy metals Pb, Ni, Zn, Mn, Cu, Cr, and Cd in 260 surface soil samples (0-20 cm) were collected and determined. Based on the soil background value in Ningxia, the soil heavy metal pollution status and potential ecological risk were evaluated through the single factor index, Nemera composite index, and potential ecological risk index, and the method of combining positive definite matrix factor analysis (PMF) and Kriging interpolation was used to analyze the soil heavy metal spatial distribution and source. The results showed that the average contents of ω (Pb), ω (Ni), ω (Zn), ω (Mn), ω (Cu), ω (Cr), and ω (Cd) were 31.42, 36.22, 62.89, 546.18, 22.26, 61.90, and 0.18 mg·kg -1 , respectively. Except for Ni, the other elements were higher than the background value of Ningxia but lower than the background value of agricultural soil pollution risk selection criteria and green food environmental quality standards. The Nemera composite index showed that the proportions of mild, moderate, and severe heavy metal pollution were 71.92%, 19.23%, and 1.54%, respectively. The potential ecological risks were mainly minor risks, accounting for 98.85%. In addition, there were a very small number of samples with medium potential ecological risk levels, accounting for 1.15% of the total number of samples. Source analysis showed that the main sources of soil heavy metals in the small watershed in the mountainous area of southern Ningxia were mixed sources of fertilization and industrial emissions (12.6%), agricultural activity sources (23.5%), natural parent material sources (27.6%), mixed sources of pesticide use and mining development emissions (17.7%), and atmospheric deposition sources (18.6%).

In order to evaluate the pollution of polycyclic aromatic hydrocarbons (PAHs) in the topsoil of the core area of the Ningdong Energy and Chemical Industry Base, 146 representative topsoil samples were collected using the grid method and the contents of 16 priority PAHs were analyzed. The results showed that the content of ΣPAHs in topsoil ranged from ND to 123.12 mg·kg -1 with an average of 10.19 mg·kg -1 . There were three high PAHs distribution areas in the northwest, southwest, and east of the core area. The source apportionment showed that the sources of PAHs in the Ningdong base were complex, and the main pollution sources were petroleum, coal combustion, traffic, and gasoline, which contributed 39.4%, 33.3%, 19.2%, and 8.1% to the total PAHs sources, respectively. The ecological risk assessment of the quality basis and quality standard method showed that the ecological impact of PAHs in the core area was slight and the possibility of negative ecological effects was low. The results of the health risk assessment showed that the order of exposure of the topsoil PAHs was skin contact > swallowing > respiratory inhalation, and the topsoil PAHs in the core area of the Ningdong base posed no potential carcinogenic risk to people of different ages.

With the acceleration of urbanization and industrialization, the content and pollution of polycyclic aromatic hydrocarbons (PAHs) in urban soils have been sources of widespread concern. Taking Shizuishan City as an example, the spatial distribution characteristics of PAHs in 156 surface soil samples (0-20 cm) from eight urban functional areas were analyzed. Single factor and Nemero composite indices, as well as a lifetime cancer risk increment model were used to evaluate PAHs pollution in soils. The sources of PAHs were analyzed using the positive matrix factorization (PMF) model. The results showed that the mean value of PAHs in the surface soil of Shizuishan City was 489.82 ng·g -1 and the coefficient of variation of 15 PAHs except for Pyr were more than 100%, indicating strong variation. The PAH contents of urban surface soils in different functional areas showed the following:traffic area (1217.61 ng·g -1 ) > industrial area (809.58 ng·g -1 ) > park (273.66 ng·g -1 ) > cultural and educational area (268.18 ng·g -1 ) > commercial area (240.05 ng·g -1 ) > agricultural area (226.81 ng·g -1 ) > medical area (211.90 ng·g -1 ) > residential area (183.49 ng·g -1 ). The Nemero composite index showed that 82.58% of the samples had no pollution, and the proportion of slight, mild, and moderate pollution were 6.45%, 4.52%, and 0.65%, respectively. Only 5.8% of the samples had serious pollution. The results of health risk assessment showed that skin contact and ingestion were the main routes of PAH exposure in soil, and the health risk was acceptable. Source analysis showed that the main sources of PAHs in Shizuishan City were traffic emissions, coal combustion, mixed biomass/heavy oil combustion, and oil sources, with contribution rates of 10.5%, 36.6%, 50.3%, and 2.6% respectively, and most of the high values were distributed in industrial or coal production areas. These results could provide reference for the study of soil pollution in industrial cities, and play an important role in preventing soil pollution, ensuring the environmental quality of the soil and human health and safety.

A total of 119 surface soil samples (depth of 0-20 cm) were collected from a Chinese wolfberry demonstration garden in Zhongning of Ningxia, and samples were analyzed for seven heavy metals (Pb, Ni, Zn, Mn, Cu, Cr, and Cd). The single factor index, comprehensive index, and potential ecological risk were used to assess the soil heavy metal contamination with the soil background values of Ningxia as the evaluation standards. The absolute principal component scores and multivariate linear regression (APCS-MLR) model as well as geostatistic analysis were combined to identify and apportion the pollution sources of soil heavy metals. The results showed that the average concentrations of Pb, Ni, Zn, Mn, Cu, Cr, and Cd in soils were 34.78, 52.376, 83.692, 641.114, 38.130, 87.257, and 0.149 mg·kg -1 , respectively. The mean concentrations of heavy metals were higher than the local soil background values but lower than the risk screening values for soil contamination of agricultural land. The comprehensive index results showed that the pollution degree of soil heavy metals was at the slightly polluted level in 81.51% of the samples, at the moderately polluted level in 16.81% of the samples, and at the unpolluted level in 1.68% of the samples. The comprehensive index values for potential ecological hazards were less than 60 in 13.45% of the samples, and these values were associated with a slight potential for ecological risks. The comprehensive index values for potential ecological hazards were less than 120 and more than 60 in 86.55% of the samples, and these values were associated with a moderate potential for ecological risks. The four main pollution sources of soil heavy metals in the study area included natural sources, industrial activity, traffic, and agricultural activity. Natural sources were the main source of Ni and Cr with average contribution rates of 55.49% and 64.66%, respectively. Industrial activity was the main source of Pb and Mn with average contribution rates of 46.93% and 42.53%, respectively. Traffic was the main source of Zn and Cu with average contribution rates of 43.51% and 53.71%, respectively. Agricultural activity was the main source of Cd with an average contribution rate of 76.79%. The study results indicated that soil heavy metals have tended to concentrate in the Chinese wolfberry demonstration garden, and the sources of heavy metals were complex and obviously influenced by human activities. Controls should be strengthened for sources that contribute to soil heavy metals to ensure the sustainable utilization of soil resources in the Chinese wolfberry land.

It is important to accurately assess the regional spatial distribution and variation of soil carbon and its fractions due to its great significance in soil carbon cycling and soil quality. The objectives of this study were to investigate the spatial variability of soil carbon and its fractions using classical and geostatistical statistics. Topsoil samples (0-20 cm) from 119 sites in Wolfberry Field were collected from a grid of 100 m×100 m in Zhongning County. The GS+7.0 software was used to fit a semivariance model to determine the optimal theoretical model and parameters. The spatial distribution characteristics of soil carbon and its fractions were studied by ordinary kriging. The classical statistical analyses showed that the average concentrations of total carbon, inorganic carbon, organic carbon, active organic carbon, medium active organic carbon, and high active organic carbon were 28.74, 18.72, 10.09, 1.81, 1.48, and 0.73 g·kg -1 , respectively. The variation coefficient of total carbon and inorganic carbon were 7.69% and 9.13%, indicating a strong variation, while the other soil carbon fractions showed moderate variation with the coefficients of variations ranging from 14.77%-52.05%. The geostatistical analyses revealed that the semivariogram of organic carbon was best fit by the spherical model, while the other five kinds of carbon fractions were best fit by the exponential model. The nugget coefficients of total carbon and organic carbon were 48.99% and 34.35%, which demonstrated moderate spatial dependence. The nugget coefficients of inorganic carbon, active organic carbon, medium active organic carbon, and high active organic carbon were 8.17%, 0.25%, 12.18%, and 0.08%, which demonstrated strong spatial dependence. The ordinary kriging interpolation map indicated that the spatial distribution patterns were similar for total carbon, organic carbon, medium active organic carbon, and high active organic carbon, which increased from southeast to northwest. Inorganic carbon and active organic carbon presented an irregular plaque distribution in the study area. Spatial interpolation maps could provide useful information for environmental management and the sustainable use of land resources in this region.

Surface soil samples (0-20 cm) from eight different functional areas in Yinchuan city were collected. There were 10 samples respectively in each functional area. The urban soil heavy metals (Zn, Cd, Pb, Mn, Cu and Cr) pollution characteristics and sources in eight different functional areas were evaluated by mathematical statistics and geostatistical analysis method. Meanwhile, the spatial distributions of heavy metals based on the geography information system (GIS) were plotted. The average values of total Zn, Cd, Pb, Mn, Cu and Cr were 74.87, 0.15, 29.02, 553.55, 40.37 and 80.79 mg x kg(-1), respectively. The results showed that the average value of soil heavy metals was higher than the soil background value of Ningxia, which indicated accumulation of the heavy metals in urban soil. The single factor pollution index of soil heavy metals was in the sequence of Cu > Pb > Zn > Cr > Cd > Mn. The average values of total Zn, Cd, Pb and Cr were higher in north east, south west and central city, while the average values of Mn and Cu were higher in north east and central city. There was moderate pollution in road and industrial area of Yinchuan, while the other functional areas showed slight pollution according to Nemoro synthesis index. The pollution degree of different functional areas was as follows: road > industrial area > business district > medical treatment area > residential area > public park > development zone > science and education area. The results indicated that the soil heavy metal pollution condition in Yinchuan City has been affected by human activities with the development of economy.

Determining spatial distributions and analyses contamination condition of soil heavy metals play an important role in evaluation of the quality of agricultural ecological environment and the protection of food safety and human health. Topsoil samples (0-20 cm) from 223 sites in farmland were collected at two scales of sampling grid (1 m x 1 m, 10 m x 10 m) in the Yellow River irrigation area of Ningxia. The objectives of this study were to investigate the spatial variability of total copper (Cu), total zinc (Zn), total chrome (Cr), total cadmium (Cd) and total lead (Pb) on the two sampling scales by the classical and geostatistical analyses. The single pollution index (P(i)) and the Nemerow pollution index (P) were used to evaluate the soil heavy metal pollution. The classical statistical analyses showed that all soil heavy metals demonstrated moderate variability, the coefficient of variation (CV) changed in the following sequence: Cd > Pb > Cr > Zn > Cu. Geostatistical analyses showed that the nugget coefficient of Cd on the 10 m x 10 m scale and Pb on the 1 m x 1 m scale were 100% with pure nugget variograms, which showed weak variability affected by random factors. The nugget coefficient of the other indexes was less than 25%, which showed a strong variability affected by structural factors. The results combined with P(i) and P indicated that most soil heavy metals have slight pollution except total copper, and in general there were the trend of heavy metal accumulation in the study area.