Search

Resource utilization and nutrient recovery of vegetable waste are necessary measures to achieve sustainable and eco-friendly agriculture. In order to determine the pollution risk and utilization potential of vegetable waste in the Huang-Huai-Hai region, we estimated the nutrient contamination load(total nitrogen(TN), total phosphorus(TP), and total potassium(TK))of vegetable waste in prefecture-level cities, through literature collation and data analysis. We used ArcGIS to characterize the spatial distribution of the comprehensive index for pollution intensity and pollution risk, of TN, TP, and TK, to identify the key areas of this region where should control nonpoint source pollution of vegetable waste. Furthermore, we examined the potential for utilization of vegetable waste resources by comparing the amount of vegetable waste with the demand for fertilizer. The results showed that in the Huang-Huai-Hai region in 2017, the total amount of vegetable waste was 16.18 million tons, with TN, TP, and TK contents of 0.42, 0.11, and 0.54 million tons, respectively;the average pollution intensity of vegetable waste was 6.45 t·hm-2·a-1, while the TN, TP, and TK pollution intensities were 15.15, 4.05, and 19.49 kg·hm-2·a-1, respectively. In the prefecture-level cities of Huang-Huai-Hai, the areas where the pollution load of vegetable waste exceeded 580 000 t·a-1 were concentrated in the central region, and included Xuzhou, Weifang, Zhoukou, Nanyang, Shangqiu and Tangshan. The pollution load accounted for 26.44% of the total load. The pollution load of TN, TP, and TK in these areas exceeded 16 000, 4000 and 19 000 t·a-1. The pollution intensity of vegetable waste exceeded 10 t·hm-2·a-1, and the cities where the pollution intensity of TN, TP, and TK exceeded 23.76, 6.36, and 31.58 kg·hm-2·a-1, respectively, included Zaozhuang, Kaifeng, Laiwu, Tangshan, Tai'an, Anyang, Jinan, Weifang, Fuyang and Shangqiu. The cities with a higher potential for utilization of vegetable waste include Weifang, Qingdao, Dezhou, Liaocheng, Linyi, Tai'an, Jining, Heze, Shangqiu, Zhoukou, and Nanyang, and account for 19.0% of the Huang-Huai-Hai region. These results can be used to inform decisions on the control, rational distribution, and comprehensive utilization of vegetable waste in the Huang-Huai-Hai region.

In order to achieve a rapid and accurate estimation of soil total nitrogen(TN) in the Taihu Lake region, the hyperspectral characteristics of TN and quantitative analysis models should be constructed to reduce potential environmental risks and provide a technical reference for precision agriculture. In this study, we acquired spectral data and TN of 93 samples with similar soil textures from a large geographical lakeshore zone in Wuxi, Jiangsu Province. Three model methods were investigated. We filtered the sensitive wavelengths using a correlation coefficient in peak value. Based on regulating soil spectral index(MSASI) arithmetic established by sensitive wavelengths, we used multivariate linear regression, artificial neural networks and partial least squares methods to construct a quantitative spectral analysis model of soil TN content. Our results indicated that total soil nitrogen content and spectral reflectance were positively correlated. We also found that sensitive wave bands, including 420~444 nm and 480~537 nm based on MSASI and multiple linear regression analysis on the sensitive wavelengths yield the best results(R2=0.98, RMSE=0.04) with high accuracy and reliability and were the best models for predicting soil total nitrogen content. The partial least squares model(R2=0.70, RMSE=0.13) and artificial neural network model(R2=0.69, RMSE=0.15) were the least accurate.