Domestic source of phosphorus to sewage treatment works.

Phosphorus is an element essential for life. Concerns regarding long-term security of supply and issues related to eutrophication of surface waters once released into the aquatic environment have led governments to consider and apply measures for reducing the use and discharge of phosphorus. Examples of source control include legislation to reduce phosphorus use in domestic detergents. This research shows that other domestic sources of phosphorus also contribute significantly to the domestic load to sewer and that overall, domestic sources dominate loads to sewage treatment works. Estimates provided here show that although the natural diet contributes 40% of the domestic phosphorus load, other potentially preventable sources contribute significantly to the estimated 44,000 tonnes of phosphorus entering UK sewage treatment works each year. In the UK, food additives are estimated to contribute 29% of the domestic load; automatic dishwashing detergents contribute 9% and potentially increasing; domestic laundry 14%, including contributions from phosphonates, but decreasing; phosphorus dosing to reduce lead levels in tap water 6%; food waste disposed of down the drain 1%; and personal care products 1%. Although UK data is presented here, it is anticipated that similar impacts would be expected for other developed economies. Consideration of alternatives to all preventable sources of phosphorus from these sources would therefore offer potentially significant reductions in phosphorus loads to sewage treatment works and hence to the aquatic environment. Combining all source control measures and applying them to their maximum extent could potentially lead to the prevention of over 22,000 tonnes-P/year entering sewage treatment works

Pharmaceuticals in soils of lower income countries: Physico-chemical fate and risks from wastewater irrigation.

Population growth, increasing affluence, and greater access to medicines have led to an increase in active pharmaceutical ingredients (APIs) entering sewerage networks. In areas with high wastewater reuse, residual quantities of APIs may enter soils via irrigation with treated, partially treated, or untreated wastewater and sludge. Wastewater used for irrigation is currently not included in chemical environmental risk assessments and requires further consideration in areas with high water reuse. This study critically assesses the contemporary understanding of the occurrence and fate of APIs in soils of low and lower-middle income countries (LLMIC) in order to contribute to the development of risk assessments for APIs in LLMIC. The physico-chemical properties of APIs and soils vary greatly globally, impacting on API fate, bioaccumulation and toxicity. The impact of pH, clay and organic matter on the fate of organic ionisable compounds is discussed in detail. This study highlights the occurrence and the partitioning and degradation coefficients for APIs in soil:porewater systems, API usage data in LLMICS and removal rates (where used) within sewage treatment plants as key areas where data are required in order to inform robust environmental risk assessment methodologies

Building Extraction from Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network

Automated methods to extract buildings from very high resolution (VHR) remote sensing data have many applications in a wide range of fields. Many convolutional neural network (CNN) based methods have been proposed and have achieved significant advances in the building extraction task. In order to refine predictions, a lot of recent approaches fuse features from earlier layers of CNNs to introduce abundant spatial information, which is known as skip connection. However, this strategy of reusing earlier features directly without processing could reduce the performance of the network. To address this problem, we propose a novel fully convolutional network (FCN) that adopts attention based re-weighting to extract buildings from aerial imagery. Specifically, we consider the semantic gap between features from different stages and leverage the attention mechanism to bridge the gap prior to the fusion of features. The inferred attention weights along spatial and channel-wise dimensions make the low level feature maps adaptive to high level feature maps in a target-oriented manner. Experimental results on three publicly available aerial imagery datasets show that the proposed model (RFA-UNet) achieves comparable and improved performance compared to other state-of-the-art models for building extraction

Distance metric choice can both reduce and induce collinearity in geographically weighted regression

This paper explores the impact of different distance metrics on collinearity in local regression models such as geographically weighted regression. Using a case study of house price data collected in Hà Nội, Vietnam, and by fully varying both power and rotation parameters to create different Minkowski distances, the analysis shows that local collinearity can be both negatively and positively affected by distance metric choice. The Minkowski distance that maximised collinearity in a geographically weighted regression was approximate to a Manhattan distance with (power = 0.70) with a rotation of 30°, and that which minimised collinearity was parameterised with power = 0.05 and a rotation of 70°. The results indicate that distance metric choice can provide a useful extra tuning component to address local collinearity issues in spatially varying coefficient modelling and that understanding the interaction of distance metric and collinearity can provide insight into the nature and structure of the data relationships. The discussion considers first, the exploration and selection of different distance metrics to minimise collinearity as an alternative to localised ridge regression, lasso and elastic net approaches. Second, it discusses the how distance metric choice could extend the methods that additionally optimise local model fit (lasso and elastic net) by selecting a distance metric that further helped minimise local collinearity. Third, it identifies the need to investigate the relationship between kernel bandwidth, distance metrics and collinearity as an area of further work

Engineering Comes Home: Co-designing nexus infrastructure from the bottom-up

The ‘nexus’ between water, food and energy systems is well established. It is conventionally analysed as a supply-side problem of infrastructure interdependencies, overlooking demand-side interactions and opportunities. The home is one of the most significant sites of nexus interactions and opportunities for redesigning technologies and infrastructure. New developments in ‘smart city’ technologies have the potential to support a bottom-up approach to designing and managing nexus infrastructure. The Engineering Comes Home was a research project that turned infrastructure design on its head. The objectives of the project were to: Demonstrate a new paradigm for engineering design starting from the viewpoint of the home, looking out towards systems of provision to meet household demands. Integrate thinking about water, energy, food, waste and data at the domestic scale to support userled innovation and co-design of technologies and infrastructure. Test new design methods that connect homes to communities, technologies and infrastructure, enhancing positive interactions between data, water, energy, food and waste systems. Develop a robust Lifecycle Assessment (LCA) Calculator tool to support environmental decisionmaking in co-design. Working with residents of the Meakin Estate in South London, the project followed a co-design method to identify requirements, analyse options and develop and test a detailed design for a preferred option. The outputs were: 1) Ethnographic study of how residents use water, energy and food resources in their homes and key opportunities for engineering design to improve wellbeing and reduce resource consumption. 2) Co-design of decentralised infrastructural systems in three workshops in 2016-2017. The first workshop identified key priorities for development from the community using a novel token-based system design method, to enable participants to build up alternative designs for local provision of water, energy, food and waste services. The second workshop provided participants with factsheets and photographs of the candidate technologies, which were then analysed using a LCA Calculator tool. 47 Rainwater harvesting was selected as the technology for further co-design in the third workshop, which focussed on scaling up a pilot installation. 3) Pilot-scale smart rainwater system was installed in partnership with the Over The Air Analytics (OTA). OTA’s system enables remote control of the rainwater storage tanks to optimise their performance as stormwater attenuation as well as non-potable water supply. 4) Lifecycle Assessment (LCA) Calculator to enable quick estimation of the impacts of new systems and technology to deliver water, energy and food, and manage waste at the household and neighbourhood scale. 5) Stakeholders, including utilities, design consultancies and community based organisations, were engaged in three workshops to inform the wider relevance and development of the co-design methods and tools. 6) Toolbox and method statements to standardise and disseminate the methods used in the project for wider application and development

Identifying the effects of land use change on sediment export: Integrating sediment source and sediment delivery in the Qiantang River Basin, China

Dramatic land use change caused by the rapid economic development in China has impacted the sediment export dynamics in the large basin. However, how land use change affects sediment export is still poorly understood. This study provided an integrated analysis of the relationships in a “three-level” chain linked as follows: “land use change → changes in sediment source and sediment delivery → sediment export change” for a better understanding. It used the InVEST sediment delivery ratio (SDR) model to analyze the Qiantang River Basin (4.27 ∗ 104 km2), China. Sediment export change was examined from the two perspectives: the effects of land use change on sediment source and on sediment delivery. Correlations between changes in individual land use types and changes in sediment source and sediment delivery were identified. The results indicated that sediment export reduced from 1.69 t ha−1 yr−1 in 1990 to 1.22 t ha−1 yr−1 in 2015 because of the decreased sediment source and a weakened sediment delivery function. In the study area, the conversions of cropland to urban land (urbanization) and bare land to forestland (afforestation) were found to make the major contributions to reductions in soil loss and SDR, respectively. Furthermore, soil loss change resulted in the decreases in total value of sediment export and SDR change caused a large-scale spatial change in sediment export. Our hotspot analysis revealed that the Wuxi River watershed should be targeted for priority conservation to optimize land use/cover for reducing sediment export. This study demonstrates the benefits of taking a comprehensive approach to analyze the processes associated with sediment export change. These allow to improve sediment management and promote aquatic ecosystem health by providing specific future land use recommendations, aimed at source treatment and delivery interception

The Future of Human-Food Interaction

There is an increasing interest in food within the HCI discipline, with many interactive prototypes emerging that augment, extend and challenge the various ways people engage with food, ranging from growing plants, cooking ingredients, serving dishes and eating together. Grounding theory is also emerging that in particular draws from embodied interactions, highlighting the need to consider not only instrumental, but also experiential factors specific to human-food interactions. Considering this, we are provided with an opportunity to extend human-food interactions through knowledge gained from designing novel systems emerging through technical advances. This workshop aims to explore the possibility of bringing practitioners, researchers and theorists together to discuss the future of human-food interaction with a particular highlight on the design of experiential aspects of human-food interactions beyond the instrumental. This workshop extends prior community building efforts in this area and hence explicitly invites submissions concerning the empirically-informed knowledge of how technologies can enrich eating experiences. In doing so, people will benefit not only from new technologies around food, but also incorporate the many rich benefits that are associated with eating, especially when eating with others

Soil sterilisation methods for use in OECD 106: How effective are they?

publisher: Elsevier articletitle: Soil sterilisation methods for use in OECD 106: How effective are they? journaltitle: Chemosphere articlelink: https://doi.org/10.1016/j.chemosphere.2018.06.073 content_type: article copyright: © 2018 Elsevier Ltd. All rights reserved

Simplifying the interpretation of continuous time models for spatio-temporal networks

Autoregressive and moving average models for temporally dynamic networks treat time as a series of discrete steps which assumes even intervals between data measurements and can introduce bias if this assumption is not met. Using real and simulated data from the London Underground network, this paper illustrates the use of continuous time multilevel models to capture temporal trajectories of edge properties without the need for simultaneous measurements, along with two methods for producing interpretable summaries of model results. These including extracting ‘features’ of temporal patterns (e.g. maxima, time of maxima) which have utility in understanding the network properties of each connection and summarising whole-network properties as a continuous function of time which allows estimation of network properties at any time without temporal aggregation of non-simultaneous measurements. Results for temporal pattern features in the response variable were captured with reasonable accuracy. Variation in the temporal pattern features for the exposure variable was underestimated by the models. The models showed some lack of precision. Both model summaries provided clear ‘real-world’ interpretations and could be applied to data from a range of spatio-temporal network structures (e.g. rivers, social networks). These models should be tested more extensively in a range of scenarios, with potential improvements such as random effects in the exposure variable dimension