Current Status and Temporal Trend of Potentially Toxic Elements Pollution in Agricultural Soil in the Yangtze River Delta Region: A Meta-Analysis

A systematic review and meta-analysis of pollutants in environmental media

Environmental pollutants are ubiquitous in our environmental media, resulting in detrimental impacts on both humans and the environment. An evidence-based review, particularly a systematic review and meta-analysis, performs a crucial function in assessing the pollution status of pollutants in environmental media at national and global scales. We selected and thoroughly investigated 76 papers focusing on systematic reviews and meta-analyses of contaminants in environmental media. The need to broaden the scope of studies was observed with an increase in the total number of publications, and there were greater focuses on food safety, water pollution, biological pollution, and environmental risks. Furthermore, this review outlined the fundamental procedures involved in a systematic review and meta-analysis, including literature searching, screening of articles, study quality analysis, data extraction and synthesis, and meta-analysis. A meta-analysis typically comprises fixed- and/or random-effects meta-analysis, identifying and measuring heterogeneity, sensitivity analysis, publication bias, subgroup analysis, and meta-regression. We specifically explored the application of meta-analysis to assess the presence of contaminants in environmental media based on two different pollutant categories, namely, non-biological and biological pollutants. The mean value is commonly utilized to assess the pooled concentration of non-biological pollutants, while the prevalence serves as the effect size of biological pollutants. Additionally, we summarized the innovative applications, frequent misuses, and problems encountered in systematic reviews and meta-analyses. Finally, we proposed several suggestions for future research endeavors.

Multidecadal heavy metals and microplastic deposition records in an urban lake: the ecological risk assessments and influencing factors

With the development of urbanization and economic growth, the urban lake ecosystem faces many challenges derived from external factors. As pollutants in the aquatic environment, heavy metals and microplastics negatively influence the urban lake ecosystem due to their intrinsic properties. To understand the distribution patterns and multidecadal deposition characteristics of heavy metals and microplastics, six sediment cores were collected in March 2021 from a Chinese urban lake, Xinghu Lake, and the isotopic composition of cesium-137 and lead-210 was analyzed for the chronology of the sediment core. Here, the classifications of comprehensive ecological risk evaluation methods for heavy metals and microplastics were adjusted further. Meanwhile, the correlations among heavy metals, microplastics, sediment grains, and natural and social factors were further analyzed. The results showed that the sediments of Xinghu Lake were mainly fine silt (39%), and the average surface area of sediment was 1.82 ± 0.60 m²/g. The average concentrations of cadmium, chromium, copper, nickel, lead, vanadium, and zinc were 0.268 ± 0.077, 59.91 ± 16.98, 23.29 ± 6.48, 52.16 ± 13.11, 36.83 ± 11.78, 119.57 ± 26.91, and 88.44 ± 29.68 mg/kg, respectively. The average comprehensive potential ecological risk indexes of heavy metals and microplastics in sediment cores were 46.59 ± 9.98 and 105.78 ± 23.32 in Xinghu Lake, and their risks were projected to reach high and very high levels by 2030 and 2050. The annual average temperature was the key natural factor for the abundances of heavy metals and microplastics, and the small sediment grain had a significant correlation with these. Agricultural activities were major pollution sources of heavy metals and microplastics, while the chemical fibers and plastic products were closely related to the abundance of microplastics.

Spatio-temporal characteristics of soil Cd pollution and its influencing factors: A Geographically and temporally weighted regression (GTWR) method

Soil Cd pollution is the result of the combined influence of various human activities over a long period of time, and then quantifying the influence is essential for the prevention and control. Based on published literature data during 2000-2020, this study investigated the pollution characteristics and influencing factors of soil Cd in the Yangtze River Delta. The results were as follows: (1) The average Cd concentration was higher than the Chinese soil criteria value (0.30 mg/kg), and the proportion of Cd concentration exceeding its background value was 87.43%. (2) The assessment results using Contamination factor (CF) and Geo-accumulation index (I_geo) indicated that the soil Cd pollution risk could not negligible in the study area. (3) The pollution center shifted significantly owing to the combined effect of human activities. (4) The main influencing factors of Cd pollution obtained by Geographically and temporally weighted regression (GTWR) model were GDP per capita, Consumption of chemical fertilizer, Output value of primary industry, and Output value of secondary industry, but there were significant differences in the dominant factors for different provinces. Our findings contribute to the current understanding of the relationship between Cd pollution and human activities, and provide a scientific basis for pollution control.

The sources risk assessment combined with APCS/MLR model for potentially toxic elements in farmland of a first-tier city, China

With the rapid economic development, potentially toxic elements (PTEs) are continuously migrating, transforming, and enriching in farmland through atmospheric deposition and other media, posing threats to food security and human health. At present, there are few quantitative studies on the health risks of PTEs sources in farmland. In this study, absolute principal component score-multiple linear regression (APCS-MLR) receptor model was used to quantify the pollution sources of PTEs in farmland in Suzhou of Yangtze River Delta Economic Zone, China. Combined with geoaccumulation index (I_geo) and health risk assessment model, the source risk of PTEs was further quantified. The results show that Cd has reached the level of unpolluted to moderate polluted (0 < I_geo < 1); the total hazard index (THI) and total carcinogenic risk (TCR) index of PTEs are acceptable for adults, but not for children (THI > 1, TCR > 1 × 10^-4). The results of APCS-MLR source apportionment were industrial sources (25.65%), agricultural sources (20.00%), traffic sources (16.81%), and domestic pollution sources (9.71%). The I_geo values of all pollution sources were less than 0, and no ecological risk was caused. The contribution patterns of pollution sources to THI and TCR in adults and children are similar. Industrial pollution sources pose the greatest non-carcinogenic risk to humans, accounting for 47.35% and 47.26% of adults and children, respectively; for carcinogenic risks, domestic pollution sources contribute the most among all identified pollution sources, accounting for 27.71% and 27.73% of adults and children, respectively. In general, this study emphasizes the need to strengthen the supervision of industrial pollution sources and domestic pollution sources in the study area to reduce the health risks to children.

Identification and risk prediction of potentially contaminated sites in the Yangtze River Delta

Identification and risk prediction of potentially contaminated sites (PCS) are crucial for the management of contaminated sites. However, the identification and risk prediction methods of PCS are lacking at a regional scale. Here, we established the fuzzy matching algorithm based on the site's name for identifying PCS in the Yangtze River Delta (YRD) from 2000 to 2020. The results showed that PCS in the YRD increased by over ten times, from 336 in 2000 to 4191 in 2020. Socio-economic and physical geography drive the growth of PCS and its spatiotemporal distribution, while the former has a more significant impact than the latter. We also presented a risk probability zoning strategy based on the source-pathway-receptor model, and proposed the patch-generating land-use simulation model to predict the risk probability of PCS in 2030. The results of risk probability zoning from 2000 to 2020 indicated that the local government of the YRD has started to pay attention to PCS management and risk control while developing social and economic. The results of risk prediction demonstrated that the proportion of low-risk probability pixels is 96.1% in 2030. Therefore, the planned indicator in the Action Plan on contaminated sites established by the State Council of China can be achieved in the YRD. Our experience in identifying and predicting PCS can inform how the local government worldwide manages PCS and tackles future challenges of achieving the ambition of site pollution control.