Annual average daily traffic estimation in England and Wales: An application of clustering and regression modelling

Collection of Annual Average Daily Traffic (AADT) is of major importance for a number of applications in road transport urban and environmental studies. However, traffic measurements are undertaken only for a part of the road network with minor roads usually excluded. This paper suggests a methodology to estimate AADT in England and Wales applicable across the full road network, so that traffic for both major and minor roads can be approximated. This is achieved by consolidating clustering and regression modelling and using a comprehensive set of variables related to roadway, socioeconomic and land use characteristics. The methodological output reveals traffic patterns across urban and rural areas as well as produces accurate results for all road classes. Support Vector Regression (SVR) and Random Forest (RF) are found to outperform the traditional Linear Regression, although the findings suggest that data clustering is key for significant reduction in prediction errors

Road Emissions in London: Insights from Geographically Detailed Classification and Regression Modelling

Greenhouse gases and air pollutant emissions originating from road transport continues to rise in the UK, indicating a significant contribution to climate change and negative impacts on human health and ecosystems. However, emissions are usually estimated at aggregated levels, and on many occasions roads of minor importance are not taken into account, normally due to lack of traffic counts. This paper presents a methodology enabling estimation of air pollutants and CO_{2} for each street segment in the Greater London area. This is achieved by applying a hybrid probabilistic classification–regression approach on a set of variables believed to affect traffic volumes and utilizing emission factors. The output reveals pollution hot spots and the effects of open spaces in a spatially rich dataset. Considering the disaggregated approach, the methodology can be used to facilitate policy making for both local and national aggregated levels

Detailed analysis of data from heat pumps installed via the Renewable Heat Premium Payment Scheme

The RHPP policy provided subsidies for private householders, Registered social landlords and communities to install renewable heat measures in residential properties. Eligible measures included air and ground-source heat pumps, biomass boilers and solar thermal. Around 18,000 heat pumps were installed via this scheme. DECC funded a detailed monitoring campaign, which covered 700 heat pumps (around 4% of the total). The aim of this monitoring campaign was to assess the efficiencies of the heat pumps and to estimate the carbon and bill savings and amount of renewable heat generated. Data was collected from 31/10/2013 to 31/03/2015. This report represents the analysis of this data and represents the most complete and reliable data in-situ residential heat pump performance in the UK to date

Assessment of the Life Cycle Environmental Impact of the Olive Oil Extraction Solid Wastes in the European Union

There is an increasing interest in developing sustainable systems in the European Union (EU) to recover and upgrade the solid wastes of the olive oil extraction process, i.e. wet husk. A Life Cycle Environmental Impact Assessment (LCIA) of wet husk has been carried out aiming at facilitating an appropriate Life Cycle Management of this biomass. Three scenarios have been considered, i.e. combustion for domestic heat, generation of electric power, and composting. The Environmental Product Declaration and the ReCiPe method were used for Life Cycle Impact Assessment. Domestic heating and power generation were the most important impact factors in damaging human health, ecosystems, and natural resources depletion. Composting was 2-4 orders of magnitude less impacting than domestic heat and power generation. Considering human health, the impact of climate change, human toxicity and particulate matter formation represented the main impact categories. Considering ecosystems, climate change and natural land transformation were the main impact categories. Within natural resources, fossil fuel depletion was impacted three orders more than metal depletion. Within domestic heating and power generation scenarios, storage of wet husk along with the extraction by organic solvent, and the waste treatment were the most impacting phases for global warming potential, ozone layer depletion, acidification and non renewable fossil resources depletion. The results obtained for the waste disposal have been comparatively assessed with respect to the environmental impact of the olive oil production chain

Honeybee-collected pollen for human consumption: impact of post-harvest conditioning on the microbiota

Bee pollen is gaining attention as functional food for human consumption. However, scanty information is available on the effects of post-harvest conditioning methods on microbial populations associated to bee pollen. Here, we assessed the microbiological quality and safety of bee-collected chestnut and willow pollen processed by different treatments, such as conventional, freeze- and microwave-assisted drying. Conventional drying of chestnut pollen significantly reduced the abundance of aerobic mesophilic bacteria and the contamination by enterobacteria and yeasts. No impact of freeze-drying and microwave-assisted conditioning was found on hygiene indicators. In chestnut pollen, microwave-assisted drying effectively reduced aerobic sporeforming bacteria, while all conditioning treatments strongly decreased coagulase-positive staphylococci. None of the conditioning methods allowed the reduction of moulds contamination and the abundance of sulphite-reducing clostridia. Our findings stress the importance of studying the microbiota of bee-collected pollen for human consumption, in order to process safe pollen with high microbiological quality

Impacts of rising temperatures and farm management practices on global yields of 18 crops

Understanding the impact of changes in temperature and precipitation on crop yields is a vital step in developing policy and management options to feed the world. As most existing studies are limited to a few staple crops, we implemented global statistical models to examine the influence of weather and management practices on the yields of 18 crops, accounting for 70% of crop production by area and 65% by calorific intake. Focusing on the impact of temperature, we found considerable heterogeneity in the responses of yields across crops and countries. Irrigation was found to alleviate negative implications from temperature increases. Countries where increasing temperature causes the most negative impacts are typically the most food insecure, with the lowest calorific food supply and average crop yield. International action must be coordinated to raise yields in these countries through improvement and modernization of agricultural practices to counteract future adverse impacts of climate change