Background: Because of the limited epidemiological evidence on the association between acute air pollutants and allergy, there is a need to investigate this association, especially between the short-term exposure to air pollution and the serum Immunoglobulin E (IgE)-mediated allergy. Methods: A total of 39,569 IgE test results and demographic characteristics were obtained in the First Affiliated Hospital of Guangzhou Medical University between August 2012 and September 2019. Ninety-nine specific allergens were tested according to clinical diagnosis. The logistic regression was used to assess the effects of CO, NO and PM exposure on the risk of sensitization to specific inhalant/food allergens. Generalized additive models with multivariate adjustments were utilized to model the exposure-response relationship. Stratified analyses were performed to estimate the reliability of correlations in various subgroups. Findings: Single-pollutant models indicate that the 3-day moving average (lag) of CO, PM or NO is associated with the increased risk for allergic diseases related to specific inhaled allergens. In multi-pollutant models, the adjusted Odds Ratio (OR) 95% (Confidence Interval, CI) increases by 8% (95% CI, 2%–15%) for per increment of 0.2 mg/m in CO levels, and rises by 8% (95% CI, 2%–13%) for each increase of 16.3 μg/m in PM concentration. The associations are stronger in youngsters (<18, years) but not significantly different by gender. Particularly, a significantly stronger association between PM exposure and hospital visits for inhaled allergy is observed in patients who are exposed to lower concentration of SO (<10.333 μg/m) and higher levels of NO (≥42.0 μg/m), as well as patients enrolled after 2017. Interpretation: The short-term exposure to CO/PM increases the number of hospital visits for IgE-mediated allergy, especially for the sensitization to specific inhalant allergens. Therefore, to prevent inhaled allergies, the public policy for controlling air pollution needs to be considered seriously. Funding: This study was supported by the University of Macau (grant numbers: FHS-CRDA-029–002–2017 and MYRG2018–00,071-FHS) as well as the Science and Technology Development Fund, Macau SAR (File no. 0004/2019/AFJ and 0011/2019/AKP). This work was also supported by the National Natural Science Foundation of China (81,871,736), the National Key Technology R&D Program (2018YFC1311902), the Guangdong Science and Technology Foundation (2019B030316028), the Guangzhou Municipal Health Foundation (20191A011073), and the Guangzhou Science and Technology Foundation (201,804,020,043).