Freshwater bodies such as lakes, rivers, and their biodiversity are being threatened with water pollution from industrial effluents and household sewages. The main objective of this study is to assess the effects of wet coffee processing plants effluent on the physicochemical and bacteriological properties of receiving rivers. Four rivers and 4 sampling points of the selected rivers were included in the study. Focus group discussion and interview were employed to gather primary data. The result showed that parameters of water quality for downstream of the rivers were significant, particularly in the dry season with BODs ranging from 45 ± 1 to 782.6 ± 97 g/ml, COD ranges from 71 ± 21 to 1072 ± 183 g/ml, Conductivity ranges from 75.5 ± 6.6 to 943 ± 56.3, Turbidity ranges from 7 ± 0.43 to 105 ± 6.2, TDS ranges from 62 ± 6.4 to 1059.6 ± 121 g/ml, temperature ranges from 20.1 to 33 ± 1, T. coli form ranges from 77 ± 1.1 to 493 ± 66 and E. coli ranges from 28 ± 1 to 213 ± 41 were significantly higher and DO ranges from 2.6 ± 0.15 to 6.1 ± 0.78 g/ml, NH4 ranges from 1.85 ± 0.4 to 3.3 ± 0.5 g/ml, and pH ranges from 3.6 ± 0.2 to 7.3 ± 0.45 were significantly lower. Most of the samples taken from wastewater and downstream parts of the river showed high level of water contaminants that are significantly greater than the EEPA discharge limits for surface water. Moreover, the qualitative data indicated that the community was affected by bad smell and color change on rivers, skin irritation, malarial case in human due to coffee processing plant effluents. Therefore, coffee processing plants should treat their effluents before they discharge it into the rivers. Responsible government bodies should authorize activities of coffee processing plants in line with the regulations set for environmental safety.

A field excavation of refusewitha short-termlandfillage from the Qingdao Xiaojianxi municipal solid waste (MSW) landfill was conducted. The physical composition and chemical properties of refuse with landfill ages of 1-4 years were studied, and the emission characteristics of odorous pollutants during the excavation period were monitored. The refuse aged 1-2 years has a higher proportion of combustible material than that the refuse aged 3-4 years, and the volatile content and calorific value in refuse aged 1-2 years were also higher than those in refuse aged 3-4 years, indicating that the refuse with a short-term landfill age was more suitable for incineration than refuse with a long-term landfill age. The pH and availablephosphorus (AP) gradually increased with increasing landfill age, while the total Kjeldahlnitrogen (TKN) and organic matter (OM) decreased. The contents of the heavy metals Cu, Zn, Ni, Pb and As generally decreased with landfill age, especially in refuse aged 2-4 years, whereas the Cr content showed no significant differences in refuse aged 1-4 years. The main odorous pollutants emitted during the excavation and screening periods were ammonia (NH3) and carbon disulfide (CS2), and the odor intensity of excavated refuse aged 1-3 years was higher than that of refuse aged 4 years. Under the condition of a small excavation area and continuous deodorization, the pollution intensity can meet the discharge standards of the factory boundary.

During the early ADME profiling the development of simple, interpretable and reliable in silico tools is very important. In this study, rule-based and QSPR approaches were investigated using a large Caco-2 permeability database. Three permeability classes were determined: high (H), moderate (M) and low (L). The main physicochemical properties related with permeability were ranked as follows: Polar Surface Area (PSA)>Lipophilicity (logP/logD)>Molecular Weight (MW)>number of Hydrogen Bond donors and acceptors>Ionization State>number of Rotatable Bonds>number of Rings. The best rule, based on the combination of PSA-MW-logD (3PRule), was able to identify the H, M and L classes with accuracy of 72.2, 72.9 and 70.6 %, respectively. Subsequently, a consensus system based on three voting binary classification trees was constructed. It accurately predicted 78.4/76.1/79.1 % of H/M/L compounds on training and 78.6/71.1/77.6 % on test set. Finally, the 3PRule and multiclassifier were validated with 23 drugs in a Caco-2 assay. The rule is very useful to improve assay design and prioritize the high absorption candidates. Meanwhile the QSPR model exhibits appropriate classification performance. Due to the simplicity, easy interpretation and accuracy, the 3PRule and consensus model developed here can be used in early ADME profiling.