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Groundbreaking New Concept to Measure Air Quality in Nanjing, China

Sino-Finnish Project Partners ▪ Vaisala Oyj is a global leader in environmental and industrial measurements. Building on 80 years of experience, Vaisala provides a comprehensive range of innovative observation and measurement products and services for weather, environmental, and industrial applications. ▪ The University of Helsinki Institute for Atmospheric and Earth System Research (INAR) carries out world-recognized A joint Sino-Finnish collaboration project will create a unique research on biosphere- demonstration environment for air quality measurement in China. atmosphere interactions The project consists of a dense air quality observation network and air quality, with a and modeling capability in the megacity of Nanjing in the Yangtze particular focus on secondary River Delta. The services and applications developed as part of the atmospheric pollution. project will provide crucial data for local air quality forecasts. ▪ Nanjing University’s School of Atmospheric Sciences is widely recognized for its A Unique Platform for Air Quality Monitoring comprehensive atmospheric research in China. The project will establish a pilot for next-generation pollution monitoring ▪ The Finnish Meteorological and modeling infrastructure in Nanjing. The project will employ Institute (FMI) is the national authority for weather services several new approaches to ambient air quality monitoring: a dense and the competent body for monitoring network based on compact air quality sensors combined air quality measurements with comprehensive observations from one stationary and one mobile in Finland. FMI carries out super site, remote sensing for vertical pollutant profiling, nanoparticulate research and consultation monitoring, and advanced fusion-based air quality modeling. A software services for air quality platform will support data dissemination to various applications. assessment and modeling globally. NETWORK OF AIR QUALITY Kunshan Yangchen Langdu AND WEATHER SENSORS ▪ Environment Institute Ltd. is a well-known environmental VAISALA NETWORK FMI ENFUSER high-tech enterprise in Jiangsu MANAGER NM10 MODELLING SYSTEM Dissemination for air quality modelling and province, specializing in the forecast web interfaces industrialization of advanced environmental technology. Climblue Technology Ltd. Open ▪ DATABASE access, utilizes satellite, in-situ, and standard Air quality model API Dissemination weather modeling data to • Data acquisition and forecast APPLICATION for citizen • Network operation analysis provide a platform for regional SERVER services and maintenance air quality analysis and management forecasting. Dense Air Quality In the Nanjing project, operational Network with 3D real-time boundary layer height Monitoring Capability data is measured with Vaisala Ceilometer CL51 and further fed An important part of the project to the air quality modeling system. is a dense air quality monitoring As a result the real-time boundary network that provides high- layer height data provides a new resolution in-situ air quality data vertical component to the air for the Nanjing region. The main quality monitoring solution. It component of the network is is also expected to improve the Vaisala Air Quality Transmitter accuracy of the modeling results. FMI-ENFUSER model AQT420. The Relationship between Weather and Air Quality block level. Forecasts are provided for up to 72 hours ahead. The Weather has a strong influence results can be used for various on local air quality; poor air decision-making purposes to quality can also influence weather. target actions aimed at improving When including critical weather air quality. Alerting and pollution Vaisala Air Quality Transmitter measurements like wind and rain in tracking are common applications AQT420, Vaisala Weather air quality monitoring stations, we that take advantage of the model´s Transmitter WXT530 Series and can better understand the sources extremely high accuracy. Vaisala Ceilometer CL51. and dispersion of the pollutants. Vaisala Weather Transmitter State-of-the-Art Data AQT420 is a compact, low-power WXT530 Series are installed in from SORPES Station instrument that measures six connection with the air quality important parameters that reveal sensors to provide critical weather The project also uses high-end the quality of the ambient air: information from a specific site. air quality data from Nanjing nitrogen dioxide (NO2), ozone SORPES (Station for Observing

(O3), carbon monoxide (CO), sulfur Modern Data Fusion Regional Processes of the Earth dioxide (SO2), and particulate Modeling System) station. SORPES is a matter (PM2.5 and PM10). Thanks to wide-scale air quality research its small size, light weight (less than FMI-ENFUSER is a unique air station of JirLATEST (Joint 1.5 kg), and low power consumption quality modeling system that International Research Laboratory (typically < 2W) it is easy to install combines traditional dispersion of Atmospheric and Earth System in a variety of locations. modeling with modern data fusion Sciences) operated by Nanjing and technologies. It fuses various Helsinki Universities. The project also introduces a datasets to model and forecast air 3D component into air quality quality in high resolution. The data The SORPES data provides monitoring by providing on-line inputs utilized in the model are unique possibilities for advanced information about the boundary typically modeled meteorological research, sensor data verification, layer height and vertical profile and regional air quality data, and network optimization. As an of the atmosphere. Together air quality and weather example, so called proxies for air with pollution emission sources, measurements, and various GIS quality variables are developed weather influences, and long-range datasets available in the city – for as part of the project. The data transportation and deposition, instance land use and traffic flow is combined to enable a deeper boundary layer height is a key data. understanding of the driving forces parameter for the characterization behind pollution episodes. of air quality. Air quality models With this methodology the model typically take boundary layer height can reach an extremely high data from weather models. modeling accuracy down to street

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