RESUMO
Catering oil fumes are a major hazard to human health. In particular, the typical Chinese cooking style is characterised by a high temperature frying process that produces high levels of cooking oil fumes. However, limited data relating to this sector mean that national emission inventory data specific to the catering service industry do not exist. To address above deficiency and thus to establish the inventory of a city, or a province, or even a country, a door-to-door survey campaign was launched in the Chinese cities of Heze and Linfen to determine the structure of local catering industries. Data revealed that the number of catering businesses per 104 people was 17 ± 4. Of these, 3.0 ± 1.4, 15.0 ± 1.4, and 82.0 ± 0.0% were classified as large, medium, and small enterprises, respectively. Furthermore, the installation rates of fume purifiers were 74 ± 13, 66 ± 9, and 51 ± 14% for large, medium, and small enterprises, respectively, with net removal efficiencies of 63 ± 11, 50 ± 7, and 31 ± 8%, respectively. This information was extrapolated across all provincial regions of China to construct a provincial and national emission inventory. In 2017, China's national catering industry released approximately 34 kt of volatile organic compounds (VOCs), 38 kt of particulate matter with a diameter less than 2.5 µm (PM2.5), 48 kt of particulate matter with a diameter less than 10 µm (PM10), 1 kt of black carbon (BC), and 27 kt of organic carbon (OC). A significant correlation was observed between vegetable oil consumption and emissions (e.g., for VOCs, y = 14.94 x + 76.50, R2 = 0.87, where y is VOCs emissions and x is vegetable oil consumption), indirectly corroborating the rationality of the inventory. Moreover, this correlation provides the potential for a dynamic inventory based on vegetable oil consumption. Future studies are proposed to address more influential factors to improve the reliability of the national inventory and refer to big data, rather than door-to-door investigation, to identify the amount of catering service businesses in a region.
RESUMO
The chemical species in PM2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM2.5 was 124 µg/m3 during the heating period, and NO3- and organic carbon (OC) were the dominant species. The concentrations and percentages of NO3-, SO42-, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.