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Abstract: Regional ozone and particulate matter (PM) pollution have a strong dependence on prevailing meteorological conditions. The occurrence of favorable conditions on a regional scale may be influenced by concurrent large scale climatic events like El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). These events evolve over inter-annual and decadal timescales and may result in variability of seasonal/annual frequency of air pollution episodes. The scarcity of measurements of criteria pollutants, especially ozone and PM, limits the scope of observing the influence of climate variability in the past few decades on regional pollution levels. To identify these trends, the frequency of occurrence of conducive conditions during the summer (ozone) and winter (PM2.5) seasons are first obtained for the period 1950–2008. The identified days are subsequently utilized in a generalized linear modeling (GLM) framework to identify the effects of ENSO and PDO on the occurrence of exceedence conducive days. To demonstrate the applicability of the developed methodology, we study the influence of ENSO and PDO on summer ozone and winter PM2.5 pollution at 6 non-attainment regions in the United States. [Copyright &y& Elsevier]

Abstract: In adaptive control of systems with poles close to the unit circle, application of the recursive estimation techniques can lead to excursions of the poles of the identified model outside the unit circle even when the process is open loop stable. These excursions can be of two types. The poles of the deterministic component of the model can drift outside unit circle even when the process has no unstable modes. Alternatively, the poles and/or zeros of the unmeasured disturbance (noise) model can drift outside the unit circle. In either case, the identified model is not suitable for on-line controller adaptation. In this work, a novel constrained recursive formulation is proposed for on-line parameter estimation based on the pseudo-linear regression (PLR) approach. The efficacy of the proposed approach is demonstrated by conducting experimental studies on a benchmark laboratory scale heater-mixer setup. The analysis of the open and closed loop experimental results reveals that the proposed constrained parameter estimation scheme provides a systematic and computationally attractive approach to ensure that the identified model parameters are restricted to the feasible region. [Copyright &y& Elsevier]

Abstract: Methods are presented to extract intra-seasonal meteorological patterns at three scales to explain 24-h fine particulate matter (PM2.5) pollution events: evolving large-scale meteorological scenarios, synoptic regimes driving diurnal variability near the surface, and localized meteorological triggers. The methods were applied to understand how winter weather conditions impacted PM2.5 around the San Francisco Bay Area (SFBA). Analyzing data across 12 winters (November–March) ensured robust characterization of the SFBA conditions. SFBA 24-h PM2.5 exceedances (35μg m−3) required several simultaneous characteristics: a ridge of aloft high pressure moving over SFBA, providing weak surface pressure gradients over Central California; persistent easterly flows through SFBA extending vertically to around the 925-hPa pressure level; orographically channeled winds resulting from stability; enhanced nocturnal cooling under clear-sky conditions providing for enhanced drainage flows off the Central California slopes; and at least two consecutive days of these conditions. [Copyright &y& Elsevier]