Emission Inventory for Israel
E. Weinrotha, M. Luriaa, A. Ben-Nunb, J. Kaplanc, M. Pelega, and I. Mahrerd
a Environmental Sciences, The HebrewUniversity of Jerusalem,
b GISCenter, The HebrewUniversity of Jerusalem
c Department of Geography, The HebrewUniversity of Jerusalem
d Faculty of Agriculture, Food and Environmental Quality Sciences, Department of Soil and Water
Abstract- High ozone levels are regularly reached during summer months over inland areas of Israel and the West Bank. Studies have been made which analyzed the back trajectories of air mass and identified the source of most of the precursors of ozone as originating from the densely populated coastline of Israel. In order to better understand the contribution of the ozone precursor emission sources, it is essential to have an accurate emission inventory, which can be used as input for a photochemical model. In the present paper, the methods used in preparing an emission inventory for Israel (for year 1998) are clarified and the results obtained are presented. From the emission inventory it is clear, that the major source of SO2 and NOx is industrial, the major source of CO are vehicles, and that VOC (Volatile Organic Compounds) originate from solvents, vehicles, industry and also vegetation. While there are many improvements that can still be made to this emission inventory, its spatial distribution and collection of most of the sources can provide a corner stone to anyone interested in running a photochemical model for the East Mediterranean area.
1. Introduction
For more than a decade elevated ozone levels, above the Israeli ambient standards have been observed during the early summer months at inland rural sites (Peleg et al., 1994; Peleg, 1997; Alper Siman Tov et al., 1997; Ranmar et al., 2001). Air mass back trajectories calculations have shown that air masses originating over Tel Aviv Metropolis caused, a few hours later the elevated mixing ratios at rural inland sites in central Israel. The precursors, carbon monoxide (CO), nitrogen oxides (NO2 and NO) and volatile organic compounds (VOC) undergo chemical and photochemical reactions in the presence of solar radiation (Seinfeld and Pendis, 1998; Finlayson-Pitts and Pitts, 1997) to create ozone, while undergoing significant mixing and transportation (Kely, 1997; Seinfeld, 1989). Photochemical models have been applied in an attempt to better understand ozone formation. These models need to take into account the variables effecting ozone formation, such as atmospheric dynamics, solar radiation, chemical and photochemical reactions and the emission inventory of primary pollutants that undergo transformation (Ziomas et al., 1994; Naresh et al., 1994; Giovannoni et al., 1995, Svensson, 1996; Sillman et al., 1997; Jacobson et al., 1997). An emission Inventory is therefore a prerequisite in order to run a photochemical model.
A study of the quantitative influence of the different air pollution sources (stationary, mobile) on ozone formation is presently under investigation in our laboratory (Weinroth et al, 2003). This study includes a simulation of the effects of the various air pollution sources (including industrial, biogenic and transportation pollutants) by use of a series of computer models which including the CAMx photochemical model (CAMx, 1998). The preparation of an extensive database for emissions from the different pollution sources, including geographical information, is a cornerstone of the study as it is a prerequisite for running the photochemical model. In the present paper methods for preparing the first overall spatial emission inventory of pollutants in Israel will be presented.
An emission inventory of greenhouse gases in Israel based on the IPCC regulations has been prepared (May-Marom and Koch, 1998). The yearly emission inventory is available on the website of the Israel central bureau of statistics ( The above emission inventories of Israel were not spatially connected.
2. Methodology
2.1 Data assimilation of the different pollution sources
The present paper summarizes the process of data collection with respect to emission rates from the various different pollution sources including, large (point) stationary sources, medium (point) stationary sources, small (area) stationary sources, biogenic (area) stationary sources, mobile (area) sources (both surface and elevated), and VOC (volatile organic compounds) solvents (line and area) sources. In those cases where emission data rates were directly available, they could be readily incorporated into the model. However in many cases, raw data was only available, and certain calculations and assumptions were required in order to convert the information available into a format suitable for incorporation into the model. The present paper outlines such calculations and the assumptions used in the preparation of the database. The data presented was updated to the year 1998.
Data regarding the exact geographical location of each emission source were also collected and integrated into the database for use within the model. This data is critical for obtaining optimal results for input into the three dimensional photochemical model. The collection and processing of the geographical data with respect to all the pollution sources is described in the following section.
2.2 Geographical location
In conjunction with collecting data relating to the emission factors, an attempt was made to ascertain the exact geographical location in three-dimensional space of the emission source.
For each stationary source, the plant’s address, if available, together with the Central Bureau of Statistics’ G.I.S. address database was used to determine the precise two-dimensional coordinates for each plant site position. In cases where the site address was unavailable, a 1:50,000-scale map was employed to identify the plant’s exact location. The emission height for each source was calculated from data available regarding output rate, emission velocity and temperature, stack diameter and height, which enabled calculating the effective stack height emission (Turner et al., 1986). The data required to calculate the effective stack heights were available for all the large stationary sources and part of the medium stationary sources.
The geographic point of emission for the aircraft emission sources was obtained by referring to the flight corridor between Ben-GurionAirport and the Mediterranean coastline as a diagonal line, and calculating the emissions as being released at the airport itself and from three points along this line, in ratios based on information provided by El-Al.
2.3 National fuel consumption - 1998
The total annual fuel consumption in Israel in 1998 was reported to be as follows: coal 1 x 1010kg; fuel oil 4.4 x 109 kg; distillate fuel 2.2 x 109 kg; diesel 2.2 x 109 kg; kerosene and naphtha 1.1 x 109 kg; LPG and natural gas 4.3 x 108 kg and oil fragments and petcock 6.7 x 108 kg.
3. Stationary Sources
3.1Major pollution sources
The principal large stationary sources in Israel are the five electrical company power plants, the Haifa and Ashdod oil refineries and the three “Nesher” cement processing plants. These sources together account for over 71% of the fuel consumption by stationary sources in Israel and 58% of its overall fuel consumption. Each of these facilities has monitors installed that record, on a per-hour per-stack basis, the quantity of the different pollutants emitted and/or the plant capacity. The locations of the large stationary point sources are indicated in figure 1.
3.1.1 Electrical Company Facilities
Equations (1) and (2), were employed to calculate the hourly SO2 and NOx emissions from the electricity producing power plants.
(1)
(2)
Where (P) is the hourly output of electricity generated, (D) the average hourly fuel consumption per output (watt), and (F) the emission rate (gm) per fuel (Kg) consumed to (F was calculated separately for SO2 and NOx).
In order to calculate CO and VOC (Volatile Organic Compounds) emissions, the amounts of fuel consumed (P*D) was multiplied by the EPA stationary sources emission factors (α) (henceforth referred to as “EPA factors”) (EPA, 1995) according to equations (3) and (4).
(3)
(4)
This necessitated the collection of data regarding the types of fuel involved since the EPA factors are fuel type sensitive. Unless otherwise stipulated, fuel type, fuel consumption, CO, SO2 and NOx emission data were collected with respect to stationary sources, were applicable, and the EPA factors were then used to calculate VOC emission factors (from fuel combustion) and also missing data for CO, SO2 and NOx emissions.
3.1.2 Haifa and Ashdod Oil Refineries
For the oil refineries, data was available with regard to the SO2 emissions and also hourly fuel consumption. Equations (1)-(4) were then employed to calculate the hourly emissions of CO, NOx and VOC as described in section 3.1.1 above.
It should be emphasized that the data available both from the Israeli Electrical Company and the Haifa and Ashdod refineries were the most accurate data available, enabling the calculation of exact hourly emission factors, whereas for all the other emission sources, hourly emissions factors could only be calculated from the available average annual data and assumptions regarding the daily and seasonal variations.
3.1.3 The “Nesher” Cement Factories Emissions
Average hourly CO, SO2 and NOx emissions were available from a limited number of measurements performed at the source by an independent company. The accuracy of this data is reasonable. However, the hourly averages calculated for Nesher, did not take into account the variations between day and night and the variations between workdays and weekends/holidays.
3.2 Medium stationary (point) sources
3.2.1 Point sources with emission reports
These sources, taken together, account for over 8.1 % of the total fuel consumption for stationary sources and 6.6% of overall fuel consumption. There are over 100 plants in this category. These plants are required by law to have their emissions monitored by an independent company once a year. The data is then reported to the Ministry of the Environment or to the Municipal Associations, who supplied this information for the present emission inventory. The data in the emission reports usually included hourly emission rates for SO2, NOx, CO and particulates. It was further assumed that during the emission measurements the plants were operating at only at 70% of full capacity. However it is reasonable to assume that these measured emission rates represent the average hourly pollution levels when taking into account the differences expected between day/night and weekdays/holidays work routines. In those cases when not all of the emissions were reported, hourly fuel consumption and fuel type data were used as a basis to calculate the missing pollutant emissions.
3.2.2 Point sources with fuel consumption reports
There are hundreds of medium plants that do not monitor their emission rates. The average hourly emissions had therefore to be calculated using the annual fuel consumption data. The fuel consumption information was obtained from The National Fuel Authority, which collects information regarding annual fuel consumption in Israel, and receives data regarding individual plant fuel consumption. The data allowed the calculation of the annual pollutant (SO2, CO, NOx and VOC species) rate emissions and hence the hourly values are therefore only an approximation, since the plant work routine is not always available. For example, some plants work at maximum capacity for 12-14 hours a day while others work at full capacity 24 hours a day but only 5.5 days a week. The plant locations are shown in Figure 1.
3.3 Small stationary sources
After taking into account the large and medium stationary sources, a myriad of small plants remain that cannot be treated as separate stationary sources, sine information regarding their individual fuel consumptions and exact geographic locations is unavailable. The small stationary sources were therefore treated as area sources. Such sources, including bakeries, electronic plants etc, use small amounts of fuel for their various manufacturing tasks. These sources account for over 15% of the fuel consumption by stationary sources and 12.2% of the overall fuel consumption.
The aggregate fuel consumption for the small stationary sources was calculated by subtracting the fuel consumption from the large and medium stationary sources from the total stationary source fuel consumption. The aggregate emissions for the above sources were then calculated using the EPA emission factors (taking into account the different fuel types). The total aggregate emission rates thus calculated were then divided uniformly over the geographical locations of the industrial areas in Israel. These industrial zones can also be seen in Figure 1.
3.4 Volatile Organic Compounds (line, area) sources
Three different sources need to be considered.
The VOC emissions from road asphalt were calculated by multiplying the length of roads in Israel (approximately 6000 km according to by the EPA ‘s emission factors of VOC emitted daily per kilometer of road.
Estimating the emissions of VOC from solvent evaporation in urban and industrial areas: paint, aerosol products, household products, adhesives (industrial and non industrial), pesticide control, space deodorant was done using the EPA factors and distributing the emissions spatially by population density.
VOC emissions also occur due to evaporation losses during transporting and marketing of petroleum liquids and gases (LPG). For LPG, this can reach up to 4% of the total amount of gas transported ( petroleum liquids EPA emission factors (EPA, 1995) were employed. These factors refer to the VOC loss at each filling stage. This occurs three times, loading of tanker from main vessel, down loading to distribution point and finally automobile fill up. The total fuel consumed was assumed to be the basis for calculating the emission rates. The calculated emission rates were distributed spatially over both urban and industrial areas.
3.4. Additional Sources
The present emission inventory does not include sources such as wood burning livestock and poultry operations, cattle feedlots, poultry farms, dairy farms, fertilizer application, and pesticide application (EPA, 1995). Based on previous studies (May-Marom and Koch, 1998), it can be assumed that the contribution of these sources to the emissions of NMHC (Non Methane Hydro Carbons) is negligible.
Household and other major heating were not included in the present study since the main purpose of the emission inventory was for ozone simulation studies. Since ozone events take place during summer time therefore the emissions from heating sources are not required.
4. Mobile sources
4.1 Ground Based Transportation
The emissions from mobile sources were evaluated as point sources using the EMME/2 Mobile5 (MOBILE5, 1994) and EMFAC7 (ARB, 1993) transportation models, and then converted into area sources (grid cells), using the GIS , which could then be inputted into the photochemical model. The above models provided emission data at three points along each transportation route – the entry and exit points of such route, and a point midway in-between. The spatial vehicular density is concentrated essentially in the Tel Aviv metropolitan area, Jerusalem and Haifa as can be seen in figure 2.
The transportation models were based on several assumptions with respect to travel time, type of travel (to work, pleasure, from work etc.), geo-economic structure of the country studied and other variables. The models also utilize an emission-vehicle speed curve (Fig. 3), derived from measurements from three different studies, FortMc-Henry (Pierson, 1996, Haifa (Tratakovsky, 1997) and Jerusalem (Yavin, 1998). The emission rate results obtained from the transportation models referred to CO, NOx and VOC.The various specific organic compounds comprising the VOC group were calculated using the percentages of VOC vehicle emission out of total VOC based on a study conducted by Kleindienst (1992). Although Kleindienst evaluated only 82% of the individual compounds, it was assumed that the organic compounds in their respective ratios also constituted the remaining 18% of the total emitted pollutants.
It should be noted that the emissions results obtained from the transportation model all related to peak morning transportation loads. In order to calculate the emissions for all hours of the day, a vehicle load versus hour of day curve for a medium sized city (Netanya 1995, Fig 4.) was employed. It is reasonable to assume that such a medium sized city represents the average between rural areas and large urban areas.
4.2 Trains
The data concerning train and railway statistics was collected from The Israel Rail Corporation ( The EPA emission factors ( were used to calculate the emissions assuming average fuel consumption per kilometer traveled.
4.3 Aviation Transportation
In order to calculate the NOx, VOC and CO emissions from civilian aviation transportation sources, information was obtained from the Israeli Aviation Administration concerning the number of daily incoming and outgoing flights from the Ben Gurion International Airport, The daily flights were divided into heavy (Boeing 757, 767 and 747 or equivalents) and medium plane categories assuming an average fleet distribution (EL-AL fleet: 65% medium sized planes 35% heavy planes). The number of flights in each category was multiplied by the appropriate fuel consumption factor, (supplied by El-Al). The fuel consumption factors relate to the fuel consumed starting from engine ignition, idling, taxing and in flight between Israel’s Ben-Gurion airport and the Israeli Mediterranean coastline. The fuel consumption thus obtained was then multiplied by the EPA emission factors in order to obtain the relevant emission rates.