[A Comparative Study of Soil Environmental Standards for Agricultural Land Among Different Countries and Its Implication for China].

Soil environmental quality of agricultural land plays a determinate role in the quality of agricultural products, human health, and the safety of the ecosystem. In 2018, China issued the "soil environment quality risk control standard for soil contamination of agriculture land" (GB 15618-2018), which has been essential to soil pollution prevention and the control of agricultural land. In this study, a systematic and comparative analysis of soil environmental standards for the agricultural land of 17 countries or regions was conducted, including the framework, protection objective, derivation method, contaminant elements, analyses methods, and standard values, as well as the impact factors. The results showed that the number of contaminants of GB 15618-2018 was insufficient with the simple consideration of total concentrations. Meanwhile, there was a lack of the standardized derivation method. On such a basis, we put forward some suggestions to improve GB 15618-2018 in light of the aforementioned problems, including strengthening the research of soil environmental benchmark and background values; establishing the scientific and standardized derivation method; and improving the number, form, and availability of indicators for risk control. In the meantime, the regional and local background environmental concentration of soil was highly proposed as a supplement and optimization to soil screening values.

[Advances in ecological risk assessment of soil in contaminated sites]. / æ±¡æŸ“åœºåœ°åœŸå£¤ç”Ÿæ€é£Žé™©è¯„ä¼°ç ”ç©¶è¿›å±•.

With the rapid urbanization and industrial structure adjustment in China, many contaminated sites have been left for remediation. It is essential to develop and implement ecological risk assessment (ERA) before remediating contaminated sites at a large scale as well as sequential management. In this review, we discussed the key problems in ecological risk assessment of soils in contaminated sites focusing on scientific principles, frameworks, techniques, and approaches, including 1) the site-specific framework, 2) uncertainty of conceptual model, 3) toxic mechanisms of combined contamination in soil, 4) screening of assessment endpoints, and 5) development of assessing approaches and frameworks. Then, two perspectives were addressed: the toxicological mechanism of soil combined pollution including bioavailability of contaminants in soil and their joint effect is the scientific problem in ecological risk assessment of soil in contaminated site; and weight of evidence approach based on USEPA four-step approach and EU Tier approach is applicable for ecological risk assessment in field conditions. Future studies should focus on: 1) the coordination of ecological risk assessment (ERA) framework and risk management framework, 2) conceptual mo-del, 3) process-based reactive transport models for exposure evaluation, 4) ecotoxicological mechanism of combined contamination in site soil, and 5) high ecological level endpoints. The aim of this review was to provide theoretical base and framework for the establishment of local guideline of ecological risk assessment in China.

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

The sand-deposition impact of artificial gravel beds on the protection of the Mogao Grottoes.

Gravel beds can prevent sand-dust emission and weaken sand-dust flux. We used wind-tunnel experiments and field observations on artificial gravel beds above the Mogao Grottoes to quantify their impact. In the report, we identified a significant correlation between gravel roughness and its ability to trap wind-transported sand. The optimal combinations of gravel diameter and coverage were determined. The greatest roughness is achieved when small gravel coverage is 75%, medium 40% and large 45%. We found that initial wind speed and gravel coverage are the key factors controlling the amount of sand trapped by the gravel beds.

[Analysis of sensitive spectral bands for burning status detection using hyper-spectral images of Tiangong-01].

To obtain the sensitive spectral bands for detection of information on 4 kinds of burning status, i. e. flaming, smoldering, smoke, and fire scar, with satellite data, analysis was conducted to identify suitable satellite spectral bands for detection of information on these 4 kinds of burning status by using hyper-spectrum images of Tiangong-01 (TG-01) and employing a method combining statistics and spectral analysis. The results show that: in the hyper-spectral images of TG-01, the spectral bands differ obviously for detection of these 4 kinds of burning status; in all hyper-spectral short-wave infrared channels, the reflectance of flaming is higher than that of all other 3 kinds of burning status, and the reflectance of smoke is the lowest; the reflectance of smoke is higher than that of all other 3 kinds of burning status in the channels corresponding to hyper-spectral visible near-infrared and panchromatic sensors. For spectral band selection, more suitable spectral bands for flaming detection are 1 000.0-1 956.0 and 2 020.0-2 400.0 nm; the suitable spectral bands for identifying smoldering are 930.0-1 000.0 and 1 084.0-2 400.0 nm; the suitable spectral bands for smoke detection is in 400.0-920.0 nm; for fire scar detection, it is suitable to select bands with central wavelengths of 900.0-930.0 and 1 300.0-2 400.0 nm, and then to combine them to construct a detection model.