In air quality forecasting systems, failure to consider the considerably large anthropogenic heat emissions generated daily in the Beijing megacity by intensive human activities is one of the major causes of model failure. In this paper, we employ the nested air quality prediction model system coupled with the weather research and forecasting model and an urban canopy model to integrate anthropogenic heat emissions over Beijing into the modeling system and exhaustively evaluate their potential effects on air quality forecast by analyzing the wind field, boundary layer structure (height and atmospheric circulation), and surface and vertical distribution of pollutants. Consequently, the effects of anthropogenic heat on the boundary layer structure, greatly pronounced in urban areas, exhibited substantial variability at different levels depending on the time. The effects were evident during both daytime and night, but played a more prominent singular role in the night in the absence of solar short-wave radiation. Basically, anthropogenic heat acts not only by directly inducing the ascent of a warm air mass from the low parts of the atmosphere over urban areas to the top of the boundary layer, but also by indirectly driving wind convergence and inducing the descent of a cooled air mass from a high altitude to the boundary layer through a complex atmospheric circulation process. Incorporating anthropogenic heat emissions into the modeling system was effective in improving predictions by reducing the normalized mean bias by 20%–30% (for wind speed) and root mean square error by 361–558 m (for boundary layer height) and by 10–23 µg m–3 (for surface PM10), with a significant reduction in the underestimation of ozone concentration by approximately 20 ppb at urban sites. This paper is expected to provide new insights into the improvement of model accuracy for air quality forecasts over megacities.