Photostationary state assumption seriously underestimates NO _x emissions near large point sources at 10 to 60 m pixel resolution

Lang Chen

Collaborative Innovation Center for Statistical Data Engineering, Technology and Application School of Statistics and Mathematics, Zhejiang Gongshang University

Zhe Song

State Key Laboratory of Natural Medicines, Jiangsu Key Laboratory of Drug Design and Optimization, and Department of Chemistry

Ningning Yao

Collaborative Innovation Center for Statistical Data Engineering, Technology and Application School of Statistics and Mathematics, Zhejiang Gongshang University

Huan Xi

Collaborative Innovation Center for Statistical Data Engineering, Technology and Application School of Statistics and Mathematics, Zhejiang Gongshang University

Jian Li

Peng Gao

Yulei Chen

Zhejiang Province Key Laboratory of Solid Waste Treatment and Recycling, School of Environmental Sciences and Engineering, Zhejiang Gongshang University

Haoyuan Su

Zhejiang Province Key Laboratory of Solid Waste Treatment and Recycling, School of Environmental Sciences and Engineering, Zhejiang Gongshang University

Yuhai Sun

Collaborative Innovation Center for Statistical Data Engineering, Technology and Application School of Statistics and Mathematics, Zhejiang Gongshang University

Boqiong Jiang

Collaborative Innovation Center for Statistical Data Engineering, Technology and Application School of Statistics and Mathematics, Zhejiang Gongshang University

Jianmin Chen

Yuanhang Zhang

College of Environmental Sciences and Engineering, Peking University

Tong Zhu

Pengfei Li

Xiaobing Pang

College of Environment, Zhejiang University of Technology

Shaocai Yu

Zhejiang Province Key Laboratory of Solid Waste Treatment and Recycling, School of Environmental Sciences and Engineering, Zhejiang Gongshang University