Search

Air quality traffic-related measures have been implemented worldwide to control the pollution levels of urban areas. Although some of those measures are claiming environmental improvements, few studies have checked their real impact. In fact, quantitative estimates are often focused on reducing emissions, rather than on evaluating the actual measures' effect on air quality. Even when air quality studies are conducted, results are frequently unclear. In order to properly assess the real impact on air quality of traffic-related measures, a statistical method is proposed. The method compares the pollutant concentration levels observed after the implementation of a measure with the concentration values of the previous year. Short- and long-term impact is assessed considering not only their influence on the average pollutant concentration, but also on its maximum level. To control the effect of the main confounding factors, only the days with similar environmental conditions are analysed. The changeability of the key meteorological variables that affect the transport and dispersion of the pollutant studied are used to identify and group the days categorized as similar. Resemblance of the pollutants' concentration of the previous day is also taken into account. The impact of the road traffic measures on the air pollutants' concentration is then checked for those similar days using specific statistical functions. To evaluate the proposed method, the impact on PM 2.5 concentrations of two air quality traffic-related measures (M1 and M2) implemented in the city of Beijing are taken into consideration: M1 was implemented in 2009, restricting the circulation of yellow-labelled vehicles, while M2 was implemented in 2014, restricting the circulation of heavy-duty vehicles. To compare the results of each measure, a time-period when these measures were not applied is used as case-control., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The accuracy and precision of air quality models are usually associated with the emission inventories. Thus, in order to assess if there are any improvements on air quality regional simulations using detailed methodology of road traffic emission estimation, a regional air quality modelling system was applied. For this purpose, a combination of top-down and bottom-up approaches was used to build an emission inventory. To estimate the road traffic emissions, the bottom-up approach was applied using an instantaneous emission model (Vehicle Specific Power - VSP methodology), and an average emission model (CORINAIR methodology), while for the remaining activity sectors the top-down approach was used. Weather Research and Forecasting (WRF) and Comprehensive Air quality (CAMx) models were selected to assess two emission scenarios: (i) scenario 1, which includes the emissions from the top-down approach; and (ii) scenario 2, which includes the emissions resulting from integration of top-down and bottom-up approaches. The results show higher emission values for PM10, NOx and HC, for scenario 1, and an inverse behaviour to CO. The highest differences between these scenarios were observed for PM10 and HC, about 55% and 75% higher (respectively for each pollutant) than emissions provided by scenario 2. This scenario gives better results for PM10, CO and O3. For NO2 concentrations better results were obtained with scenario 1. Thus, the results obtained suggest that with the combination of the top-down and bottom-up approaches to emission estimation several improvements in the air quality results can be achieved, mainly for PM10, CO and O3., (© 2013 Elsevier B.V. All rights reserved.)

Benzene is a carcinogenic and genotoxic pollutant which mainly affects the people health through the inhalation. Nevertheless, this pollutant is not frequently measured by air-quality networks. To solve this problem, some models have been published to estimate benzene concentrations in the atmosphere. However, the lack of measures makes difficult the application of complex models in order to get a detailed spatio-temporal analysis, namely in urban areas. In this work was developed a simple semi-empirical model to predict benzene concentrations based on the ratio of benzene and carbon monoxide concentrations in order to predict the concentrations of this pollutant in large areas and periods with lack of benzene measurements but with higher impact in the human health. The model was applied to an urban area, the Metropolitan Area of Oporto, for a period of 12 years (1995-2006). Monthly correlations between benzene and carbon monoxide concentrations at Custóias air-quality station are significant (p = 0.01) and higher in winter (r(s) > 0.7) than in summer (0.3 > r(s) > 0.7). Estimate of the monthly ratio of the concentration of these two pollutants range between 199 and 305. The methodology validation shows good results (r(s) = 0.81) which allow, assuming the availability of carbon monoxide data, the use of this tool for areas with low benzene recorded data. The application of this methodology in the study area shows an annual average trend decrease of benzene concentrations during the study period, which may be linked to a general trend decrease of benzene emissions in European urban areas, including the study domain.

E-commerce growth is raising the demand for logistic activities, especially in the last-mile, which is considered the most ineffective part of the supply chain and a negative externalities source. Although various solutions aim to address these issues, selecting the best one is challenging due to multiple perspectives, conflicting criteria, trade-offs, and complex and sensitive urban contexts. This article proposes a 4-level hierarchical model based on the triple bottom line of sustainability that may assist decision-makers in selecting the most adequate last-mile solution for historic centers. The model was defined based on a systematic literature review; evaluated by interviewing a set of experts; and quantified according to an AHP-TOPSIS approach. This quantification focused on the historic center of Porto, Portugal. The experts considered all three sustainability dimensions similarly important. Air pollution was the most valued sub-criterion whereas Visual pollution was the least. 67 decision-maker profiles were defined, showing that environmentally oriented decision-makers prefer cargo bikes, while decision-makers who prioritize economic and social factors prefer parcel lockers. All last-mile solutions considered in the model yielded similar results, therefore suggesting a combined distribution strategy. Nevertheless, the use of parcel lockers is the most favorable solution for Porto's historic center. • The group of experts considered the three sustainability dimensions equally important. • Air pollution is the most valued criterion, whereas Visual pollution is the least. • Cargo bikes are more interesting for environmentally oriented decision-makers. • Parcel lockers are the most favorable solution and seem adequate in Porto. • A combined last-mile distribution strategy might be the most optimal alternative. [ABSTRACT FROM AUTHOR]

As part of a larger research project to assess the influence of benzene on public health of Oporto Metropolitan Area, a methodology to estimate the population exposure to this pollutant has been developed and applied. The benzene concentrations recorded in the municipality of residence and the number of pendular movements, have a major influence on the estimation of the population exposure to this pollutant. [ABSTRACT FROM AUTHOR]