A dataset of logistics sites in England and Wales: Location, size, type and loading bays.

Data on the location and size of logistics sites is essential for the accurate system-level modelling of transport and logistics operations. This is becoming increasingly important to support governments and industry transition to a net zero future which will feature new operating models and vehicle technologies, particularly for electric vehicle operations. In this work we present a dataset of logistics sites across England and Wales categorised into warehouses, retail sites, and factories. There are 47,683 rows of data in total, comprising 27,691 warehouse sites, 6,441 retail sites, and 13,551 factory sites. Each row contains the site's category, location (latitude and longitude), size (in square meters), and modelled number of heavy goods vehicle loading bays. Raw data on non-domestic properties in England and Wales were sourced from the UK's Valuation Agency Office database. Addresses were geocoded to determine the coordinates of each site, floor area was determined for each site via a web crawler script, and the type of site was derived using a keyword-based categorisation process. The size of the site gives an indication of the expected transport activity (i.e. volume of goods handled) and is a useful proxy to estimate the number of loading bays which, in turn, is a useful proxy for the number of electric heavy goods vehicle charging points the site may have to accommodate to support electric vehicle operations. Models relating the floor area to the number of loading bays were developed using satellite imagery of a sample of data from each category. Uncertainty in the geolocation, category and floor area data is deemed to be very low<1%), while the models to predict loading bay data are based on a sample of the overall dataset and subject to higher uncertainty (<20 %). Larger sample datasets and alternative models may be explored in future work to suit other applications.

Greenhouse Gas and Noxious Emissions from Dual Fuel Diesel and Natural Gas Heavy Goods Vehicles.

Dual fuel diesel and natural gas heavy goods vehicles (HGVs) operate on a combination of the two fuels simultaneously. By substituting diesel for natural gas, vehicle operators can benefit from reduced fuel costs and as natural gas has a lower CO2 intensity compared to diesel, dual fuel HGVs have the potential to reduce greenhouse gas (GHG) emissions from the freight sector. In this study, energy consumption, greenhouse gas and noxious emissions for five after-market dual fuel configurations of two vehicle platforms are compared relative to their diesel-only baseline values over transient and steady state testing. Over a transient cycle, CO2 emissions are reduced by up to 9%; however, methane (CH4) emissions due to incomplete combustion lead to CO2e emissions that are 50-127% higher than the equivalent diesel vehicle. Oxidation catalysts evaluated on the vehicles at steady state reduced CH4 emissions by at most 15% at exhaust gas temperatures representative of transient conditions. This study highlights that control of CH4 emissions and improved control of in-cylinder CH4 combustion are required to reduce total GHG emissions of dual fuel HGVs relative to diesel vehicles.

Biocompatibility: meeting a key functional requirement of next-generation medical devices.

The array of polymeric, biologic, metallic, and ceramic biomaterials will be reviewed with respect to their biocompatibility, which has traditionally been viewed as a requirement to develop a safe medical device. With the emergence of combination products, a paradigm shift is occurring that now requires biocompatibility to be designed into the device. In fact, next-generation medical devices will require enhanced biocompatibility by using, for example, pharmacological agents, bioactive coatings, nano-textures, or hybrid systems containing cells that control biologic interactions to have desirable biologic outcomes. The concept of biocompatibility is moving from a "do no harm" mission (i.e., nontoxic, nonantigenic, nonmutagenic, etc.) to one of doing "good," that is, encouraging positive healing responses. These new devices will promote the formation of normal healthy tissue as well as the integration of the device into adjacent tissue. In some contexts, biocompatibility can become a disruptive technology that can change therapeutic paradigms (e.g., drug-coated stents). New database tools to access biocompatibility data of the materials of construction in existing medical devices will facilitate the use of existing and new biomaterials for new medical device designs.