Generating traffic flow and speed regional model data using internet GPS vehicle records.

Nowadays, many smart-phones and vehicles are equipped with Global Position System (GPS) for tracking and navigation purposes, providing an opportunity to derive highly representative local vehicular flow and estimate vehicular emissions information. Here, we report and discuss methods used to handle large volumes of such activity data, namely 124 million GPS recordings from the web page Maplink.com.br, extract high spatial resolution vehicular flow information for a vast area in South-east Brazil, and correct for bias using traffic counts observations for the same area. The method consists in filter speed and accelerations, assign buffers to the road network, aggregate speed by street, fill missing number of lanes, generate traffic flow. Methods presented here were used to inform traffic-related air quality modelling and used as part of local air pollution management activities but are also amenable to any work that would be enhanced by more locally representative or time-resolved inputs for traffic flow, e.g. traffic network management, and demand modelling. •124 million GPS observations from electronic devices were used to generate traffic flow.•Spatial bias was investigated and accounted for using independent local traffic count data.•Traffic count rescaled GPS traffic flow provide a robust description of spatial and quantitative traffic patterns.

Landfill siting based on optimisation, multiple decision analysis, and geographic information system analyses.

Sanitary landfill remains the most common methodology for final treatment and disposal of municipal solid waste worldwide, the cost per tonne depends on its scale. The bigger the landfill, the cheaper the cost of treatment, so the consortium of municipalities is the solution to achieve an economic scale. However, the growth of waste production introduces pressure for adequate solutions and therefore has been increasing sanitary landfill site selection studies. This study proposes a methodology for siting sanitary landfills and optimising the transport of municipal solid waste for a locality in the state of São Paulo, Brazil. Environmental, social, and economic criteria were established. Their correlated attributes were categorised into suitability levels and weighted according to multiple decision analysis. The data were organised and mapped within a geographic information system. Considering sites where landfills are prohibited, two scenarios were generated. The Mixed-Integer Quadratic Programming mathematical model is used to minimise the costs of transporting municipal solid waste and operating sanitary landfills. In Scenario 1, the results indicated that 64% of the area was suitable as a potential sanitary landfill site, 9% of the area exhibited medium suitability, and 27% of the area was classified as restricted. In Scenario 2, the results indicated that 25% of the area was suitable as a potential sanitary landfill site, 4% of the area had medium suitability, and 71% of the area was classified as restricted. The optimal solutions for Scenario 1 and Scenario 2 enabled sites to be determined for five landfills and four landfills, respectively.