Estimation of commercial cooking emissions in real-world operation: Particulate and gaseous emission factors, activity influencing and modelling

Pengchuan Lin; Jian Gao; Wanqing He; Lei Nie; James J Schauer; Shujian Yang; Yisheng Xu; Yuanxun Zhang

doi:10.1016/j.envpol.2021.117847

Estimation of commercial cooking emissions in real-world operation: Particulate and gaseous emission factors, activity influencing and modelling

Environ Pollut. 2021 Nov 15:289:117847. doi: 10.1016/j.envpol.2021.117847. Epub 2021 Jul 26.

Authors

Pengchuan Lin¹, Jian Gao², Wanqing He³, Lei Nie³, James J Schauer⁴, Shujian Yang⁵, Yisheng Xu², Yuanxun Zhang⁶

Affiliations

¹ State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
² State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
³ Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, Beijing Municipal Research Institute of Environmental Protection, Beijing, 100037, China.
⁴ Environmental Chemistry and Technology Program, University of Wisconsin-Madison, Madison, WI, 53706, USA; Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, 53718, USA.
⁵ College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
⁶ College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen, 361021, China; Yanshan Earth Critical Zone and Surface Fluxes Research Station, University of Chinese Academy of Sciences, Beijing, 101408, China. Electronic address: yxzhang@ucas.edu.cn.

PMID: 34388553
DOI: 10.1016/j.envpol.2021.117847

Abstract

Measurements of real-world cooking emission factors (CEFs) were rarely reported in recent year's studies. However, the needs for accurately estimating CEFs to produce cooking emission inventories and further implement controlling measures are urgent. In this study, we collected cooking emission aerosols from real-world commercial location operations in Beijing, China. 2 particulate (PM_2.5, OC) and 2 gaseous (NMHC, OVOCs) CEF species were examined on influencing activity conditions of cuisine type, controlling technology, operation scales (represented by cook stove numbers), air exhausting volume, as well as location and operation period. Measured NMHC emission factors (Non-barbecue: 8.19 ± 9.06 g/h and Barbecue: 35.48 ± 11.98 g/h) were about 2 times higher than PM_2.5 emission factors (Non-barbecue: 4.88 ± 3.43 g/h and Barbecue: 15.48 ± 7.22 g/h). T-test analysis results showed a significantly higher barbecued type CEFs than non-barbecued cuisines for both particulate and gaseous emission factor species. The efficacy of controlling technology was showing an average of 50 % in decreasing PM_2.5 CEFs while a 50 % in increasing OC particulate CEFs. The effects of controlling equipment were not significant in removing NMHC and OVOCs exhaust concentrations. CEF variations within cook stove numbers and air exhausting volume also reflected a comprehensive effect of operation scale, cuisine type and control technology. The simulations among activity influencing factors and CEFs were further determined and estimated using hierarchical multiple regression model. The R square of this simulated model for PM_2.5 CEFs was 0.80 (6.17 × 10^-9) with standardized regression coefficient of cuisine type, location, sampling period, control technology, cook stove number (N) and N² of 5.18 (0.02), 5.33 (0.02), 1.93 (0.19), 9.29 (4.18 × 10^-6), 9.10 (1.71 × 10^-3) and -1.18 (2.43 × 10^-3), respectively. In perspective, our study provides ways of better estimating CEFs in real operation conditions and potentially highlighting much more importance of cooking emissions on air quality and human health.

Keywords: Control technology; Cooking emission factors; Particulate and gaseous pollutants; Real-world emission modelling.

MeSH terms

Air Pollutants* / analysis
Cooking
Environmental Monitoring
Gases
Humans
Particulate Matter* / analysis

Substances

Air Pollutants
Gases
Particulate Matter