RESUMEN
Traffic emissions are an important source of air pollution worldwide, but in the Middle East, this problem is exacerbated by weak or no enforcement of emission regulations. Comprehensive measurements of fine PM emission factors (EFs) from road transport in the region have not yet been conducted, but such data are necessary for quantitative assessments of the health impact of transport emissions in the region. To address this need, PM2.5 samples collected inside the Salim Slam tunnel in Beirut, Lebanon were analyzed for carbonaceous matter (organic carbon (OC) and elemental carbon (EC)), water-soluble ions, elements, and selected organic compounds. The OC/EC ratio was 1.8 for the total fleet and 2.6 for light-duty vehicles (LDV), in agreement with the dominant proportion of gasoline LDV in the Lebanese fleet. A Cu/Sb ratio of 4.2±0.1 was observed, offering a valuable metric for detecting brake wear emissions in subsequent studies conducted in the region. The EFs of carbonaceous matter, elements and ions generally varied by a factor 0.1 and 10 in comparison to literature values, while those for alkanes and polycyclic aromatic hydrocarbons were similar to the upper values previously reported. The average number size distribution was characterized by a single mode around 35 nm. The particles number EF (for diameters between 10-480 nm) was within the range of 1014-1015 particles per kg of fuel. The chemical mass balance model showed an average contribution to EF of 62% from non-exhaust sources. This study highlights the need for more enforceable stringent vehicular regulations because of the local practices (i.e., removal of catalyst) and some EF values are very high compared to other studies/countries.
RESUMEN
Urban greenhouse gas emissions monitoring is essential to assessing the impact of climate mitigation actions. Using atmospheric continuous measurements of air quality and carbon dioxide (CO2), we developed a gradient-descent optimization system to estimate emissions of the city of Paris. We evaluated our joint CO2-CO-NOx optimization over the first SARS-CoV-2 related lockdown period, resulting in a decrease in emissions by 40% for NOx and 30% for CO2, in agreement with preliminary estimates using bottom-up activity data yet lower than the decrease estimates from Bayesian atmospheric inversions (50%). Before evaluating the model, we first provide an in-depth analysis of three emission data sets. A general agreement in the totals is observed over the region surrounding Paris (known as Île-de-France) since all the data sets are constrained by the reported national and regional totals. However, the data sets show disagreements in their sector distributions as well as in the interspecies ratios. The seasonality also shows disagreements among emission products related to nonindustrial stationary combustion (residential and tertiary combustion). The results presented in this paper show that a multispecies approach has the potential to provide sectoral information to monitor CO2 emissions over urban areas enabled by the deployment of collocated atmospheric greenhouse gases and air quality monitoring stations.