## 1 Introduction  
Atmospheric aerosols have important impacts on climate, air quality and human health [1; 2; 3]. Their properties are highly variable in both space and time. Space-based platforms provide a global view of the aerosol system, unmatched by any other measurement system in terms of the spatial coverage [4]. With the long-history of aerosol products derived from the Moderate resolution Imaging Spectroradiometer (MODIS) and the aging of the instrument, there is programmatic interest in continuing similar aerosol retrieval capabilities. Since the launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011, there has been great interest in retrieving aerosol properties from VIIRS [5; 6; 7].  
Currently, there are multiple algorithms available for deriving aerosol optical depth (AOD) and other aerosol properties from VIIRS data [6; 8]. Here, we consider two. The VIIRS Environmental Data Record (VIIRS_EDR) is being produced by the United States National Oceanic and Atmospheric Administration (NOAA) [6]. At the same time, the National Aeronautics and Space Administration (NASA) is considering long-term continuity for developing an aerosol climate data record. For this purpose, [PERSON] et al. are experimenting with a \"MODIS-like\" dark-target algorithm for use on VIIRS data (VIIRS_ML) [8]. How does each of these algorithms perform for retrieving AOD and other aerosol properties over China, a region of extreme diversity of aerosol sources, compositions, and loadings?  
Preliminary evaluation of VIIRS_EDR and VIIRS_ML derived AOD, has been performed separately using co-located sunphotometer data from the AErosol Robotic NETwork (AERONET) and other networks [9]. For the period of 1 May 2012-30 April 2013, [PERSON] et al. showed VIIRS_EDR underestimated the AOD over land with global mean bias of \(-0.02\)[6]. However, the Suomi NPP VIIRS aerosol data product assessment report showed VIIRS_EDR overestimated the AOD in land of 0.06 to 0.11 for the period of 1 May 2012-14 October 2012 [10]. In addition, larger biases were found in western Asia and India [9]. Since experimental VIIRS_ML has only been available since 2015, the evaluation is limited. [PERSON] et al. briefly validate the VIIRS_ML AOD at 550 nm by comparing it to AERONET observations from March 2013 to February 2014 and showed VIIRS_ML overestimates the AOD over land with global positive bias of 0.005 [8].  
The above studies have limited scope in that they only provide estimates of the global expected error over land. They do not focus on evaluating products over regional scales, especially where AERONET data are sparse. Hence, the focus of this study is to evaluate VIIRS_EDR and VIIRS_ML data over the North China Plain (NCP: 114-120\({}^{\circ}\)E, 34.5-41\({}^{\circ}\)N), one of the most densely populated regions in China that has experienced enormous economic growth in past two or three decades [11; 12; 13; 14]. Indeed, the NCP is one of the most severely polluted areas in the world with frequent heavy haze events in recent years [11; 15; 16]. Given that retrieved aerosol optical properties are often used as a proxy for assessing climate and air quality in the NCP region, a regional validation of VIIRS aerosol products has important consequences [12; 17; 18].  
The organization of this paper is as follows. We introduce the VIIRS instrument and the two aerosol retrieval algorithms and corresponding data in Section 2. The validation data set and methods for inter-comparison are in Section 3. The AOD evaluation results are presented in Section 4. Section 5 states the aerosol model types and the optical properties comparison between the CE318 sunphotometer and VIIRS, including VIIRS_EDR and VIIRS_ML. The conclusions are presented in Section 6.