Particulate matter (PM) air pollution poses a formidable public health threat to the city of Beijing. Among the various hazards of PM pollutants, microorganisms in PM2.5 and PM10 are thought to be responsible for various allergies and for the spread of respiratory diseases. While the physical and chemical properties of PM pollutants have been extensively studied, much less is known about the inhalable microorganisms. Most existing data on airborne microbial communities using 16S or 18S rRNA gene sequencing to categorize bacteria or fungi into the family or genus levels do not provide information on their allergenic and pathogenic potentials. Here we employed metagenomic methods to analyze the microbial composition of Beijing’s PM pollutants during a severe January smog event. We show that with sufficient sequencing depth, airborne microbes including bacteria, archaea, fungi, and dsDNA viruses can be identified at the species level. Our results suggested that the majority of the inhalable microorganisms were soil-associated and nonpathogenic to human. Nevertheless, the sequences of several respiratory microbial allergens and pathogens were identified and their relative abundance appeared to have increased with increased concentrations of PM pollution. Our findings may serve as an important reference for environmental scientists, health workers, and city planners.

Conventional Model Reference Adaptive Controller (MRAC), while providing an architecture for control of systems in the presence of parametric uncertainties, offers no means for characterizing the system's input/output performance during the transient phase. Application of adaptive controllers was therefore largely restricted due to the fact that the system uncertainties during the transient have led to unpredictable/undesirebale situations, involving control signals of high-frequency or large amplitudes, large transient errors or slow convergence rate of tracking errors, to name a few. In this paper, we develop a novel adaptive control architecture that ensures that the input and the output of an uncertain linear system track the input and output of a desired linear system during the transient phase, in addition to the asymptotic tracking. This new architecture has a low-pass filter in the feedback-loop that enables to enforce the desired transient performance by increasing the adaptation gain. For the proof of asymptotic stability, the L 1 gain of a cascaded system, comprised of this filter and the closed-loop desired reference model, is required to be less than the inverse of the upper bound of the norm of unknown parameters used in projection based adaptation laws. The ideal (non-adaptive) version of this L 1 adaptive controller is used along with the main system dynamics to define a closed-loop reference system, which gives an opportunity to estimate performance bounds in terms of L ∞ norms for both system's input and output signals as compared to the same signals of this reference system. Design guidelines for selection of the low-pass filter ensure that the closed-loop reference system approximates the desired system response, despite the fact that it depends upon the unknown parameters. The tools from this paper can be used to develop a theoretically justified verification and validation framework for adaptive systems. Simulation results illustrate the theoretical findings.

The urban heat island (UHI), the phenomenon of higher temperatures in urban land than the surrounding rural land, is commonly attributed to changes in biophysical properties of the land surface associated with urbanization. Here we provide evidence for a long-held hypothesis that the biogeochemical effect of urban aerosol or haze pollution is also a contributor to the UHI. Our results are based on satellite observations and urban climate model calculations. We find that a significant factor controlling the nighttime surface UHI across China is the urban–rural difference in the haze pollution level. The average haze contribution to the nighttime surface UHI is 0.7±0.3 K (mean±1 s.e.) for semi-arid cities, which is stronger than that in the humid climate due to a stronger longwave radiative forcing of coarser aerosols. Mitigation of haze pollution therefore provides a co-benefit of reducing heat stress on urban residents.

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