Abstract: Beijing Regional Environmental Meteorology Prediction System (BREMPS) is established by coupling BJ-RUC, WRF-Chem and preferred visibility parameterization scheme. The performance test with observations in 2014 and Asia-Pacific Economic Cooperation (APEC) period shows that BREMPS has a good forecasting ability for two important elements in air quality and haze forecasting in Beijing and surrounding area, PM_2.5 concentration and visibility. Correlation coefficients of PM_2.5 between forecasted and observed values reaches above 0.6 at most sites, and even reaches above 0.8 at some sites in Beijing. Forecasted values generally underestimate the PM_2.5 concentrations with a regional average normalized mean bias of-15%. The forecast performance shows slight decrease after 24 forecasted hours. Comparing with the regional average, the forecast performance is best in Beijing urban area and northern of Hebei. The forecasted PM_2.5 concentration agrees well with the observation in Beijing area. Correlation coefficients of PM_2.5 concentrations between forecasted and observed values in 48 forecasted hours are about 0.77 in urban area. The normalized mean bias is generally in a range of-26%. The correlation coefficient in rural area is higher than that in urban area. However, the mean bias is also higher in rural area. That is probably attributed to the inaccuracy of the emission information in these areas. The forecast performance is better in spring, autumn and winter, during which the correlation coefficient between forecasted and observed values mostly ranges from 0.7 to 0.9, and the normalized mean bias is within 20%. The forecasted visibility is closer to automatic measurements than artificial observations. Forecasted values are in good agreement with observations during sustained low visibility synoptic processes. For the hourly visibility lower than 10 km, the accuracy of forecast is 77%, which decreases with the reduction of visibility and reaches 40% when the visibility is lower than 2 km. BREMPS shows good forecast performance during the APEC period, when the temporal evolutions of AQI and visibility, and spatial distribution of PM_2.5 concentrations are well forecasted, providing strong support for the environmental meteorology forecast service.