Rare earth slag fromSouth Jiangxi,China, was prepared into a promising low-cost adsorbent (CRES) through carcination for phosphorus removal in phosphorus over-loaded wastewater. To characterize CRES systematically, a number of modern equipment, such as Scanning Electron Microscope (SEM), Infrared Spectroscopy (FTIR), X-ray Fluorescence (XRF), Specific Surface Area Analyze (BET-BJH) and Thermogravimetric Analysis (TGA) were used. Phosphorus adsorption and desorption processes of CRES were studies by means of adsorption isotherm and adsorption kinetics.Effect of pH of the solution on P adsorption by CRES was also explored. Results show that CRES has a well-developed porous structure, containing various metal elements and metalloid element compounds, such as Ba, V, Si, Y, Ca, Fe, Yb, etc., on its surface. Solution pH, ranging from 2.2 to 10.0, did not affect much on its P adsorption capacity. Additionally, desorption of phosphorus-loaded CRES was investigated in different aqueous solutions. It was found that the P desorption rate was much higher in HCl solution than in any other others.The Langmuir modelwas found to be good in describing the P adsorption isotherm (R² = 0.9325，n = 5) of CRES. Themaximum PO₄^3-adsorption capacityof CREScould be as high as 152 mg•g^-1, higher than any other adsorbents’ previously reported. P adsorption kinetics tests reveal that the P adsorption reached equilibrium pretty soon, only after 4 - 6 min, of which the process could be well described with Ho’s pseudo-second-order kinetic model, implying that chemisorption was the dominant mechanism of the P adsorption. Chemisorption was related to surface functional groups of CRES and coordination effect. Further, physisorption was also involved in this adsorption process, but mainly occurred at the initial stage of the adsorption process. Physisorption was related to various metal/metalloid elements contained in the surface as well as the well developed porous structure of CRES.

The Kaihui River watershed was selected as study area, where 12 ponds were sorted into 3 types: Type I,ponds excavated out of farmland in recent years; Type II,, ponds at the foot of hills under intense human disturbance; Type III, ponds at the foot of hills under little human disturbance. Water quality, physic-chemical properties of sediment and phosphorous adsorption behavior in sediment of the ponds were analyzed relative to type of pond. Results show that the three types of ponds followed an order of TypeⅠ﹥Ⅱ﹥Ⅲ in concentration of total P, oxalate extracted P, inorganic P of all other forms (excepted NH₄Cl-P), and bio-available P, which corresponded to the order of the ponds in water pollution degree. Among the inorganic forms of phosphorous, an order was found of metal oxide bound P (NaOH-P)﹥calcium bound P (HCl-P)﹥reducible P (BD-P)﹥loosely sorbed P (NH₄Cl-P) in terms of concentration. NaOH-P was the dominant form, accounting for 68.51%. Concentrations of BD-P and HCl-P were significantly and positively related to Fe_ox (P<0.01), while the concentrations of NH₄Cl-P and NaOH-P were to Al_ox (P<0.05). Fitting of P adsorption with the Langmuir equation found that the equilibrium P concentration (C_0EP), maximum sorption (S_max), and adsorption constant (K_c) in the sediments of the 12 ponds ranged from 0.02 - 0.12 mg·L^-1, 526.32 - 826.45 mg·kg^-1, and 0.31 - 1.11 L·mg^-1, respectively. The sediment in Pond 6 (TypeⅠ) was the highest in C_0EP and the lowest in S_max and K_c, so tha, it was the highest in potential P releasing risk. Pond 10 and Pond 11 (TypeⅡ) were quite high in K_c and S_max and relatively low in C_0EP. Pond 3 varied between Type I and Type II in P adsorption capacity. It is, therefore, quite obvious that the input of extraneous pollutants through human activities has a certain impact on P content and P adsorption behavior in the sediments of the ponds in the study area, and that in controlling P pollution in headwater regions of agricultural watersheds, it is essential to put P input load and P adsorption capacity of pond sediments under consideration.

A pot experiment was conducted to study effects of phosphorus and silicon on migration of Pb in the soil-tobacco system and to explore approaches to reducing Pb activity in soil and Pb concentration in tobacco leaf. Results show that phosphorus application made exchangeable and carbonate-bound Pb transformed into Fe-Mn oxide-bound and residual Pb in non-rhizospheric soil and silicon application made exchangeable Pb transformed into Fe-Mn oxide-bound Pb. Combined application of phosphorus and silicon made exchangeable Pb transformed into Fe-Mn oxide-bound, organic-bound and residual Pb. Though tobacco roots tend to activate Pb in the rhizosphere, the application of P, Si and P+Si in combination reduced the content of exchangeable Pb in the rhizosphere by 46.05%, 14.24% and 48.76%, respectively, and hence reduction of Pb uptake of tobacco by 44.02%，44.04%，and 65.65%, respectively, thus lowering the concentration of Pb in tobacco leaf by 63.06%, 60.37%, and 83.24%, respectively. P application restricted the transportation of Pb from soil to tobacco leaf by reducing the mobility index of Pb from soil to root (I_Msoil-root) and that from root to stem (I_Mroot-stem) as well. Si application and combined P and Si application restricted the transportation of Pb from soil to tobacco leaf by reducing I_Msoil-root, I_Mroot-stem and I_Mstem-leaf, (the mobility index of Pb from stem to leaf). Application of P and Si is an effective measure to reduce Pb concentration in tobacco leaf, and combined application of P and Si is more effective than the application of merely P or Si.

In order to determine quality of the ambient air in solar greenhouses and its variation pattern, three solar greenhouses, different in operation age, (1, 5 and 10a), were chosen for monitoring of indoor temperature, relative humidity, Cl₂, NH₃, NO, O₃, inhalable particle (PM₁₀) and total suspended particles (TSP), using the in-situ fixed site monitoring method. And on such a basis, quality of the indoor air was evaluated.  Results show that the temperature, relative humidity, concentrations of Cl₂, NH₃, NO and O₃ inside the greenhouses were closely related to the outside meteorological conditions, and the concentration of suspended particles increased with the operation age of the greenhouse. Diurnal and monthly variations of Cl₂, NH₃, NO and O₃ did not differ much between greenhouses different in age. The highest concentrations of Cl₂, NH₃ and O₃ occurred at about 14:00, while that of NO did around the times of mat uncovering and covering, NO was negatively correlated with O₃ in concentration (r =﹣0.964). The daily mean concentrations of Cl₂ and the highest concentrations of NH₃ in the greenhouses, regardless of age, all exceeded the national standard, but those of O₃ and NO did not. In terms of concentration of PM₁₀ and TSP, the 10a greenhouse was the highest, and followed by the 5a greenhouse and 1a greenhouse. The concentration of PM₁₀ and TSP in January and February was the highest in a year, and especially in the 10a greenhouse, where PM₁₀ exceeded the national standard for indoor air quality.

With a farmers’ welfare evaluation index system established based on Amartya Sen’s capability approach, and the fuzzy comprehensive evaluation method, a case study was performed of Ezhou and Xiantao, Hubei Province to evaluate changes in farmers’ welfare as a result of concentration of living (inhabitaregion). Results show that the farmers’ welfare decreased somewhat in level both in the two regions, and fuzzy evaluation indicates a drop from 0.455 and 0.442 to 0.373 and 0.366, respectively. From the perspective of functional activities, their social resources, housing conditions and living environment all improved, however, their economic conditions, guarantee of rights and interests and psychological emotion deteriorated in different degrees. Among all the functional activities, family economic conditions and guarantee of rights and interests varied the most significantly and were the major contributors to the decline of their welfare. From the angle of conversion factors, their education level, proportion of dependent population and regional differences all had some impacts changing the farmers’ welfare.