Baltimore Supersite: Highly time- and size-resolved concentrations of urban PM2.5 and its constituents for resolution of sources and immune responses

Protection of public health from the effects of air particulate matter (PM) requires measurements and methods that assess the PM chemical constituents, physical properties, and their sources. Sampling was conducted at three sites in the Baltimore area: a source-oriented (industrial) area in south Baltimore (FMC site), and two receptor area sites (Clifton Park and Ponca Street). FMC measurements were made for the initial 1-month of the project; Clifton measurements lasted for about 2 months, while measurements at Ponca Street lasted for about 9.5 months. Pollutant samples were collected at intervals ranging from 5 min to 1 h using semi-continuous monitors for PM2.5 mass, sulfate, nitrate, elemental and organic carbon, particle number size distributions (10–20,000 nm), CO, NOx, O3, 11 metals, and mass spectra of individual particles, throughout the project. In addition to standard meteorological measurements, a 3D-sonic anemometer and a LIDAR system were operated during selected periods as were a rotating drum impactor with 3- to 6-h resolution and a filter/PUF sampler for 3-h measurements of organic compounds. Standard speciation and FRM mass measurements were also made. This report describes the types of measurements that were made at the various sites of the Baltimore Supersite program as well as presents the summary statistics for some of the PM measurements that have been made. The measurements of aerosol mass, major components, and size distribution data for the three sites are compared. Results show comparable PM concentrations at Ponca Street and Clifton Park. Increased variability was observed at Ponca Street

Estimation of PM10-bound As, Cd, Ni and Pb levels by means of statistical modelling: PLSR and ANN approaches

Air quality assessment regarding metals and metalloids using experimental measurements is expensive and time consuming due to the cost and time required for the analytical determination of the levels of these pollutants. According to the European Union (EU) Air Quality Framework Directive (Directive 2008/50/EC), other alternatives, such as objective estimation techniques, can be considered for ambient air quality assessment in zones and agglomerations where the level of pollutants is below a certain concentration value known as the lower assessment threshold. These conditions occur in urban areas in Cantabria (northern Spain). This work aims to estimate the levels of As, Cd, Ni and Pb in airborne PM10 at two urban sites in the Cantabria region (Castro Urdiales and Reinosa) using statistical models as objective estimation techniques. These models were developed based on three different approaches: partial least squares regression (PLSR), artificial neural networks (ANNs) and an alternative approach consisting of principal component analysis (PCA) coupled with ANNs (PCA-ANN). Additionally, these models were externally validated using previously unseen data. The results show that the models developed in this work based on PLSR and ANNs fulfil the EU uncertainty requirements for objective estimation techniques and provide an acceptable estimation of the mean values. As a consequence, they could be considered as an alternative to experimental measurements for air quality assessment regarding the aforementioned pollutants in the study areas while saving time and resources.The authors gratefully acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness through the Project CMT2010-16068. The authors also thank the Regional Environment Ministry of the Cantabria Government for providing the PM10 samples at the Castro Urdiales and Reinosa sites