ects of flow regime on biofilm community composition and functions.The interpretive utility of environmental magnetic proxies for investigating airborne particulate matter (PM) pollution impact is restricted by differences in soil composition, land cover and land use. For soil magnetic applications, land use strongly influences magnetic particle distribution down the soil profile, even in homogeneous soil environments. Here, an adaptive approach is engineered to provide accurate magnetic proxy information for pollution monitoring across different land use types. In an 81-km2 area between two industrial harbours, the irregular distribution of forests, arable lands, pasture and residential areas prevented robustly relating topsoil magnetic susceptibility data to known pollution impacts. Although normalized topsoil susceptibility values showed improved potential for deriving airborne pollution impacts, optimal results were obtained by depth-integrating magnetic susceptibility logs, revealing long-term impacts of both active and decommissioned industrial facilities. Complementing soil magnetic observations, active and passive (bio)magnetic monitoring allowed discriminating short-term pollution patterns and evaluating changes in PM impact across the study area. Hereby, active PM receptors (strawberry leaves and plastic coated cardboards (PCCs)) provided promising results, yet passive receptors allowed estimating pollution impacts more efficiently. For the latter, species-independent grass leaf sampling reflected airborne PM depositional patterns most accurately, whereas wiped anthropogenic surfaces proved too sensitive to wash-off.Governments in many developing countries, such as China, are investing a lot of human, financial and material resources to ensure that as much of municipal solid waste (MSW) as possible is collected for centralized harmless treatment and disposal. This is regarded as an effective way to alleviate the "waste siege" problem in governance caused by the continuous enormous increase in MSW quantity. Therefore, how to improve the efficiency of MSW collection service system is an important governance issue because the inputs that can be utilized to manage MSW problem are limited due to budget and resource constraints. https://www.selleckchem.com/products/bay-2927088-sevabertinib.html However, studies on MSW collection efficiency in developing countries like China are under-represented in the existing literature. This paper applies a stochastic frontier analysis (SFA) approach to evaluate the efficiency of MSW collection services in 30 provinces of China from 2008 to 2017, and explore the relative importance of several factors that might influence collection efficiency. The results indicate that there exists considerable room (62.8%) to enhance efficiency since its current efficiency value is merely 0.372. With regard to influencing factors, the proportion of population aged 15-64 appears to have the greatest positive impact on efficiency, along with per capita GDP, added value of tertiary industry and education level. This paper also explores spatial variations of MSW collection efficiency across the eastern, central and western regions. These findings have policy implications and can inform the related government departments how to formulate proper policies to improve collection efficiency.In recent decades, water quality problems that impact human health, especially groundwater pollution, have been intensely studied, and this has contributed to new ideas and policies around the world such as Low Impact Development (LID) and Superfund legislation. The fundamental to many of these problems is pollutant occurrence and migration in saturated porous media, especially in groundwater. Such environments often contain contrasting zones of high and low permeability with significant differences in hydraulic conductivity (~10-4 and 10-8 m/s, respectively). High-permeability zones (HPZs) represent the primary pathways for pollutant transport in groundwater, while low-permeability zones (LPZs) are often diffusion dominated and serve as both sinks and sources (i.e., via back-diffusion) of pollutants over many decades. In this review, concepts and mechanisms of solute source depletion, contaminant accumulation, and back-diffusion in high- and low-permeability systems are presented, and new insights gained from both experimental and numerical studies are analyzed and summarized. We find that effluent monitoring and novel image analysis techniques have been adroitly used to investigate temporal and spatial evolutions of contaminant concentration; simultaneously, mathematical models are constantly upscaled to verify, optimize and extend the experimental data. However, the spatial concentration data during back-diffusion lacks diversity due to the limitations of pollutant species in studies, the microscopic mechanisms controlling pollutant transformation are poorly understood, and the impacts of these reactions on contaminant back-diffusion are rarely considered. Hence, most simulation models have not been adequately validated and are not capable of accurately predicting pollutant fate and cleanup in realistic heterogeneous aquifers. Based on these, some hypotheses and perspectives are mentioned to promote the investigation of contaminant migration in high- and low-permeability systems in groundwater.Water resource development opens up opportunities for improving smallholder farmer livelihoods in sub-Saharan Africa; however, implementation of water resource interventions to ensure sustainability hinges on the availability of sufficient quantity and quality data for monitoring, analysis and planning. Such data is often acquired through instrumentation of water resources (e.g. stream flow monitoring) or the use of hydrological models. In sub-Saharan Africa, data scarcity has limited the ability to monitor and make appropriate decisions for water resource allocation and use. Data derived from remote sensing has been considered a viable option to fill this gap; however, there is limited research in the region that evaluate the quality of the remotely sensed based datasets. This study evaluated actual evapotranspiration (AET) estimates derived from Advanced Very High Resolution Radiometer (AVHRR AET) images and Moderate Resolution Imaging Spectrometer (MOD16 AET) images using estimates from a grid-based Soil and Water Assessment Tool (SWAT).