Design of Georeference-Based Emission Activity Modeling System ( G-BEAMS ) for Japanese Emission Inventory Management

It comes near to stating the obvious to say that an emission inventory is essential to understanding the status of pollutant emissions and to designing comprehensive countermeasures for mitigating them. To improve the accuracy of an inventory and to allow data management, it is necessary to develop methods for systematizing an emission inventory. We developed an emission inventory system, the Georeference-Based Emission Activity Modeling System (G-BEAMS). The primary function of our system is to estimate the spatial and temporal distributions of chemical emissions and air pollutants in Japan. It uses mathematical functions to estimate emissions; emissions maps to show differences over time; and databases of emission factors, activity data, spatial weighting factors, and temporal weighting factors. G-BEAMS standardizes emission-source categories and geographic position. Unfortunately, there is no Japanese standard source classification for an emission inventory like the US SCC (Source Classification Code) or the EU SNAP (Selected Nomenclature for Air Pollution) code. Therefore, we coded our own classification by considering a combination of industries, production processes, and production technologies. Geographic positions were defined with polygonal, linear geometry or coordinate values on a GIS layer; each geometry has a unique index. Basic layers in the system were chosen with regard to the public availability of statistical data, including geographic position information. This standardization enables us to systematize procedures for compiling an emission inventory by both top-down and bottom-up approaches, and by spatially and temporally allocating estimated emissions. 13th International Emission Inventory Conference in Clearwater, Florida, June 7 10, 2004 2 INTRODUCTION An emission inventory helps us to quantify the status of environmental burdens. Compiling an emission inventory by emission source is useful for figuring out not only the total environmental burden, but also the contribution of each source to the total. Moreover, an emission inventory showing the geographical distribution of emissions (an “emission map”) can supply input data to atmospheric dispersion and environmental fate models. From the outputs of these models, we can evaluate environmental impacts of emission sources. Knowing this helps us to manage environmental risks and to design policy measures to reduce them. Evaluation of the effects of countermeasures needs recompilation of the emission inventory, to reflect changes in emission factors and related activities. Systematizing the procedures for building an emission inventory facilitates such recompilation. So far, however, most emission inventories compiled in Japan have been static, and methods of systematizing inventories have not been discussed sufficiently. The methods for and approaches to estimating emissions depend on the type of environmental burden and the emission source; hence, it can be very difficult to develop a systematized method independent of burden and source, as for all inventory processes. However, as proposed by the US EPA (Ryan, 2003), procedures needed in emission inventorying can be classified into four steps: emission estimation, temporal allocation, spatial allocation, and pollutant speciation. In order to systemize an emission inventory, it is important to focus on these common fundamental procedures. The primary aim of our study was to develop a system to compile an emission inventory (an inventory system). This paper describes its design; in particular, system configuration, techniques of data management, and key methods corresponding to the formulation of emission estimation. We roughly classify the fundamental procedures to build an emission inventory into three steps: estimation of emissions, estimation of spatial distribution, and estimation of temporal distribution. In line with these estimation procedures, the following section explains the characteristics of our system design and methods. MATERIALS AND METHODS System configuration and data management As essential data on emission activity, for each entry, an inventory system needs to assign an emission source category, geographical location, and an emission estimation method. To manage these data, we use a geographical information system (GIS) and database software. Figure 1 illustrates the system configuration. The emission source categories are identified by a unique code. Because of the lack of a standard system for coding emission sources in Japan like the SCC in the USA and SNAP in the EU, we devised our own code, the Hierarchical Source Classification Code, or HSCC. Under the HSCC, each emission source can be categorized by the combination of three type codes representing industry, industrial process, and technology. The geographic position is preliminarily defined by geometry on a GIS layer. The system prepares standard layers and gives a unique code (the LinkID) to each geometry on a layer (Suzuki et al., 2003). Since geometry in a GIS is a figure having geographical position and shape, we can handle emission locations by LinkIDs. A GIS is a powerful tool for mapping emission distributions. G-BEAMS calculates emissions from the corresponding HSCC and LinkID and saves the results in the database. Considering the public availability of Japanese statistics applicable as emission activity data, we 13th International Emission Inventory Conference in Clearwater, Florida, June 7 10, 2004 3 selected 13 standard type layers (Suzuki et al., 2003). These layers are summarized in Table 1. Handling emission activity data with LinkIDs enables us to manage them with just database software, because the actual location of an emission source can be identified by converting its LinkID into geometry on the layer in the GIS. Methods for estimating emissions take the form of functions written in computer language. By using a common format for inputting data with LinkID into the function and outputting the result with LinkID from it, G-BEAMS allows accumulation, choice, and replacement of various estimation methods. Understandably, defining geographic position by geometry has the disadvantage of limiting the geographical resolution of an emission inventory. But the geographical resolutions of our standard layers can cover those of most Japanese social statistics applicable to activity data; therefore, G-BEAMS can be used to build inventories of various pollutants. Figure 1. Schematic of configuration of G-BEAMS Table 1. Speciation of predefined geometries on the standard layer in the inventory system 1. Emission activity (Database software) 3. Estimation methods (Programming function) 2. Location (GIS) Predefined geometry given unique number (LinkID) 100001 100002 100004 100005 100006 100007 100008