h i g h l i g h t sVOCs, NO 2 , SO 2 and O 3 were measured around a densely populated industrial zone. Five separate weekly passive sampling campaigns were conducted at 55 locations. The spatial distribution of pollutants extracted in PMF were used to realize sources. Six factors were identified using a large number of chemical species available. The cancer risk due to benzene inhalation was calculated using Monte Carlo simulation. a r t i c l e i n f o a b s t r a c t Ambient concentrations of volatile organic compounds (VOCs), nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ) and ground-level ozone (O 3 ) were measured at 55 locations around a densely populated industrial zone, hosting a petrochemical complex (Petkim), a petroleum refinery (Tupras), ship-dismantling facilities, several iron and steel plants, and a gas-fired power plant. Five passive sampling campaigns were performed covering summer and winter seasons of 2005 and 2007. Elevated concentrations of VOCs, NO 2 and SO 2 around the refinery, petrochemical complex and roads indicated that industrial activities and vehicular emissions are the main sources of these pollutants in the region. Ozone concentrations were low at the industrial zone and settlement areas, but high in rural stations downwind from these sources due to NO distillation. The United States Environmental Protection Agency's positive matrix factorization receptor model (EPA PMF) was employed to apportion ambient concentrations of VOCs into six factors, which were associated with emissions sources. Traffic was found to be highest contributor to measured P VOCs concentrations, followed by the Petkim and Tupras. Median cancer risk due to benzene inhalation calculated using a Monte Carlo simulation was approximately 4 per-one-million population, which exceeded the U.S. EPA benchmark of 1 per one million. Petkim, Tupras and traffic emissions were the major sources of cancer risk due to benzene inhalation in the Aliaga airshed. Relative contributions of these two source groups changes significantly from one location to another, demonstrating the limitation of determining source contributions and calculating health risk using data from one or two permanent stations in an industrial area.