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Natural ventilation (NV) is a key sustainable solution for reducing the energy use in buildings, improving thermal comfort, and maintaining a healthy indoor environment. However, the energy savings and environmental benefits are affected greatly by ambient air pollution in China. Here we estimate the NV potential of all major Chinese cities based on weather, ambient air quality, building configuration, and newly constructed square footage of office buildings in the year of 2015. In general, little NV potential is observed in northern China during the winter and southern China during the summer. Kunming located in the Southwest China is the most weatherfavorable city for natural ventilation, and reveals almost zero loss due to air pollution. Building Energy Simulation (BES) is conducted to estimate the energy savings of natural ventilation in which ambient air pollution and total square footage must be taken into account. Beijing, the capital city, displays limited per-square-meter saving potential due to the unfavorable weather and air quality for natural ventilation, but its largest total square footage of office buildings makes it become the city with the greatest energy saving opportunity in China. Our analysis 1 † These authors contributed equally to this work.

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In this paper, we design real-time decentralized and distributed control schemes for Heating Ventilation and Air Conditioning (HVAC) systems in energy efficient buildings. The control schemes balance user comfort and energy saving, and are implemented without measuring or predicting exogenous disturbances. Firstly, we introduce a thermal dynamic model of building systems and formulate a steady-state resource allocation problem, which aims to minimize the aggregate deviation between zone temperatures and their set points, as well as the building energy consumption, subject to practical operating constraints, by adjusting zone flow rates. Because this problem is nonconvex, we propose two methods to (approximately) solve it and to design the real-time control. In the first method, we present a convex relaxation approach to solve an approximate version of the steady-state optimization problem, where the heat transfer between neighboring zones is ignored. We prove the tightness of the relaxation and develop a real-time decentralized algorithm to regulate the zone flow rate. In the second method, we introduce a mild assumption under which the original optimization problem becomes convex, and then a real-time distributed algorithm is developed to regulate the zone flow rate. In both cases, the thermal dynamics can be driven to equilibria which are optimal solutions to those associated steady-state optimization problems. Finally, numerical examples are provided to illustrate the effectiveness of the designed control schemes.