Ranking of Industrial Products2 Results2.1 Assessment of calculation results2.2 Uncertainties of results 2.3 Overall assessment 2.1 Assessment of calculation resultsThe result of the calculations appears from appendices 1a and 1b. The calculations in appendix 1a are based on the mean value of volumes of production and supply, whereas the calculations in appendix 1b are based on volumes of supply only. In both appendices 1a and 1b all commodity groups are stated according to their final weighted ranking, which allows for both loss of resources and energy consumption. Additionally the following information is given for all commodity groups:
It should be noted that more commodity groups may have the same ranking, and further that appendix 1a includes all commodity groups, whereas in appendix 1b only the approx. 200 highest ranked commodity groups - to save space - are included. Below the results of the most interesting of the approx. 50 highest ranked commodity groups are commented on: As regards the 50 highest ranked commodity groups there is only a small difference in the lists in appendices 1a and 1b. In practice 44 repetitions can be registered. The six commodity groups from appendix 1a, which are not included in the 50 first groups in appendix 1b, can be found among no. 50 to 82 in appendix 1b. As regards the upper 50 commodity groups there is thus no significant difference as to whether the ranking is based on volumes of supply exclusively or on the mean value of volumes of production and supply. In reality these are products, which are sold in very large quantities or in other ways involve a loss of resources and/or energy consumption so high that this will be perceptible in both cases. Even though the upper 50 commodity groups represent many different types of industrial products and in reality also semi-manufactures and raw materials, there is a fairly clear picture of the sectors of society that are interesting, when the topic is loss of resources and energy consumption. The energy sector The first sector that leaps to the eye is the energy sector. This sector is among the 50 upper commodity groups represented by the following groups: 27003 Pit coal It can be discussed whether these goods should be considered industrial products or semi-manufactures/raw materials. As they are included here, it is natural that they are placed at the top of this list because of the large quantities used and consumed (i.e. are lost). Even though the calculation of the energy consumption for these commodity groups is not accurate (in the calculation it is assessed that 60% of the energy content is utilised, whereas the real figures are 40% for pit coal and 80 - 90% for other fuels), the results reflect nevertheless the fact that a significant part of the energy of these fuels is not utilised. The greater part of the calculated energy consumption reflects in reality the energy that is lost. The transport sector The next sector appearing is the transport sector. This sector is among the 50 upper commodity groups represented by the following groups: 89003 Oceangoing cargo vessels The above are all industrial products of long life and considerable energy consumption during their use phase. The loss of resources of these products is however not insignificant. For ships that are predominantly made of iron and steel (which are recyclable without any problems), lubricating oils and other system liquids for motors etc. are the dominant part of the loss of resources. Cars and trains have relatively larger contents of plastic and other materials that are not - or only to a limited extent - reusable. Generally it should be noted that the results show that the transport sector is one of the most significant energy consumers, which is due to the heavy transportation demands in the Danish community as it is organised today. The extent to which the energy consumption for carrier vessels and refrigerator ships can rightfully be considered harmful to the Danish community and environment could of course be a subject of discussion, as these ships are mainly used in international trade, and their use therefore is not related especially to the Danish community. As to cars, it should be considered how the energy consumption could be reduced (lightweight materials, more energy-efficient motors?) simultaneously with an increase of the share of recyclable materials. Agriculture A third important sector is agriculture and related industries, among others the fertilizer and the food industries. This sector is among the 50 upper commodity groups represented by the following groups: 31006 Mixed fertilizers Generally these goods are included, because they are sold in very large quantities. As regards fertilizers, these are based on raw materials, which are here considered non-renewable resources. Phosphorous minerals are in themselves a geological resource, whereas ammonia, which is also the basis material of the greater part of the nitrogenous fertilizers - is considered a non-renewable resource, as the hydrogen contained in ammonia is today produced from fossil fuels. If the hydrogen were instead manufactured by electrolytic dissociation of water, the ammonia would be considered a renewable resource. The energy consumption for manufacture of meat can predominantly (cf. material data in appendix 6 for the material "a250 Meat from mammals") be traced back to agriculture‘s consumption of energy for feeding stuff, heating, ventilation etc. The high ranking of so many products related to agriculture draws focus to agriculture‘s nitrogen balances (nitrogenous fertilizers as well as manure), but also to the fact that agriculture‘s entire meat production in reality involves a significant loss of energy, when energy in vegetable raw materials is converted to meat products. Building and civil trade The building and civil trade is represented among the upper 50 commodity groups by the following products: 25011 Cement The high ranking of these products is primarily due to the fact that they are sold in very large quantities. Some of these products (cement and steel reinforcement) are in reality predominantly semi-manufactures, e.g. used for manufacture of concrete goods. At the calculation of loss of resources for concrete it was taken into consideration that 70% (cf. appendix 6) is estimated to be reused, substituting new gravel and stone/gravel aggregates for road building. It might of course be a subject of discussion whether gravel and stone are a resource that the community should be just as concerned about as other resources. On the other hand it must be assessed that the loss of resources in any case represents a considerable need for landfill capacity that should be minimised in the interest of the society. An overall assessment is that the result points in the direction that a continued improvement of the reuse of concrete, and a minimisation of the energy consumption at the manufacture of cement and concrete should be given high priority. Because of the comprehensive quantities concerned even minor improvements would be of great importance in relation to many other products. Goods of gypsum and rock wool are high-ranked, partly because of the large quantities and partly because there is no recycling of these goods meaning that the entire consumption in reality represents a loss of resources. Asphalt and bitumen-containing mixtures cover predominantly asphalt layers for roads. In the calculation the significant reuse of old asphalt occurring today was taken into consideration. In spite of that, the loss of resources and the energy consumption are however still considerable. That means - as in connection with concrete - that even minor improvements would be of great importance in relation to many other products. The consumption sector Industrial products for households and ordinary consumption are represented among the upper 50 commodity groups by the following groups: 84021 Refrigerators, upright and home freezers The high ranking of refrigerators, washing machines, television etc. is first and foremost due to the energy consumption during use. The result shows that there is every reason to continue the present efforts to promote the development and the use of low-energy equipment. For washing machines the loss of resources has however also a relatively high importance. Measured throughout the life of a washing machine, detergents and softeners account for 86% of the total material quantity for a washing machine, whereas the machine and the belonging packaging are only 14%. It is thus evident that possible efforts in connection with washing machines should focus on the function of the machine (i.e. consumption of soap etc.) rather than on the materials, of which the machine is composed. Furniture of wood-fibre boards and similar products (includes all types of furniture based on chipboards and wood-fibre boards), papers and magazines and bottled beer are high-ranked primarily because of the large quantities. For papers and magazines the calculated loss of resources is solely related to the printing ink. For bottled beer the loss of resources is related to the cap and the small share of beer bottles that is not reused, neither as bottle nor material. For furniture the picture is much more diffuse, as besides the wood-fibre and chipboards a wide selection of renewable as well as non-renewable materials - including various veneer, plastic and metal materials, paints and lacquers for surface treatment, edges etc. - are used. It should be evaluated whether there are reasons to consider how the share of renewable materials could be increased (can e.g. printing ink be produced exclusively from renewable materials?), and whether it would be possible to reduce the energy consumption for the manufacture processes. Carrier bags etc. of plastic materials as well as aluminium foil are transport and packaging articles used for a series of purposes. The high ranking provides a reason to consider - among other things - whether recycling arrangements for the materials included in these commodity groups should be established. Lighting accessories (lamps, fittings) are high-ranked, because the energy consumption of the incandescent lamps, fluorescent tubes etc. for the entire life of the lamp/fittings is included. Thus the focus is directed to the role of the lamp/fittings as light source and to the means (reflectors, energy-saving light bulbs etc.) available for optimization of the energy utilization. Machines and engines The last sector to be underlined her is machines and engines for industrial processes etc. Among the upper 50 commodity groups are the following: 84005 Engines with compression ignition (i.e. diesel motors) The reason for the underlining of these commodity groups is the common characteristics that even though the quantity of the industrial product itself is quite modest, the commodity groups are nevertheless high-ranked as regards both loss of resources and energy consumption. In any case these are industrial products of a considerable consumption of working means and energy during use. Motors are high-ranked on the list partly because of considerable energy consumption, partly because of a large consumption of lubricating oil for the continuous maintenance. The result shows that an improvement of the efficiency of the motors should generally be given high priority. Textile processing machines include machines for washing, bleaching, dyeing, rolling up, cramping, starching, impregnation and other finishing treatment of textiles. Except machines for rolling up and cramping, these machines all have large consumption of water and various chemical substances. The weighted composition of this commodity group is estimated to 99% chemical substances and 1% other, which in this connection covers the iron etc. of which the machines are made. In practice the result places focus on the fact that textile production is an area with a large consumption of chemicals, water and energy. The result for casting machines shows correspondingly that casting processes require a very large consumption of moulding sand and energy, whereas vending machines (with primarily beverages) are high-ranked because of a large consumption of disposable drinking cups and the energy consumption for heating/cooling of beverages. The remaining commodity groups Among the first mentioned 50 commodity groups it is relatively easy to identify the most important sectors. The picture is however more dim concerning the commodity groups further down the list. Actually products from different sectors are listed, depending on quantities and characteristics of each commodity group. As already registered for the 50 upper commodity groups the characteristics placing a commodity group high on the list will be as follows:
It should be noted however that also products predominantly consisting of renewable materials (e.g. foodstuffs) can be high-ranked on the list. When this is the case, it is mainly due to packaging of non-renewable materials (e.g. plastic materials and metal), and that the product is sold in so huge quantities that even a modest packaging share of a few percentage of the total weight of the product results in considerable amounts of non-renewable resources. As it appears from the following section the calculated result of the loss of resources of such products must however be considered very uncertain. 2.2 Uncertainties of resultsThe ranking of commodities is subject to uncertainty, because all the data applied for the estimates of loss of resources and energy consumption are to some extent uncertain. In this section an assessment of the uncertainties and their importance to the ranking is made. Initially it should be stressed that all assessments of uncertainties made here are based on an estimate, as the true and real data are not available. The uncertainty calculation made in the following is based on the assumption that for almost all types of data (e.g. volume of production, correction factor, loss of resources of materials) the predominant part of the data quantity was determined with a relatively modest uncertainty, whereas a minor part of the data quantity had a high degree of uncertainty, sometimes even considerably high. As an example it can be mentioned that it is assessed here that the uncertainty of the ASC values (energy consumption for extraction and manufacture of materials) is dividable as follows:
The above division expresses that for most materials (roughly estimated 75%) many studies for determination of ASC values have already been carried out, and even though these data are old, and it was necessary to project these, the uncertainty can generally be considered limited. The uncertainty degree is highest at the data estimated by enthalpy calculations, or estimated by analogy to other data, or covers material groups in reality consisting of many different materials with widely different ASC values. Additionally there are the uncertainties based on the fact that the material list lacks defined materials covering the materials of which the industrial product actually consists. Here it was chosen to grade these uncertainties by assessing that for 20% of the materials the value will be very uncertain (±100%), whereas the remaining 5% of the materials is quite wrong, which is here expressed by an uncertainty interval of -100% to +500%, as the ASC value cannot become negative. Irrespective of the precise reasons for uncertainty of the individual ASC values, it is difficult to make an absolute and positive estimate of the uncertainty of the individual value. For ASC values based on studies in literature it is as mentioned assessed that the uncertainty generally is limited. This does not mean however the uncertainty of all data of this type is limited. It can be expected that the majority of such values do not deviate significantly from the truth (i.e. a low uncertainty), whereas a minority will deviate much (i.e. high uncertainty). The situation is the contrary for data based on enthalpy calculations, conclusion by analogy etc. Here the majority of data must be expected to deviate much from the truth (i.e. high uncertainty), whereas a minority will deviate a little (i.e. low uncertainty). This means that the only quite safe way to evaluate uncertainties is for each ASC value to evaluate and tabulate a statistical distributional function describing the uncertainty of precisely this value and thereafter find a method for assessing the resulting uncertainties. This procedure would involve a workload of the same size as the one already invested in this project. An alternative might be to carry out sensitivity calculations on the results by changing selected values. Because of the many different data included in this project, such sensitivity calculations might seem of accidental character (what data should be changed?) or alternatively result in a calculation practice of an enormous scope with results that would actually be difficult to interpret. In this project it was chosen to consider all ASC values a group of data, about which there are some uncertainties describable through a statistical distributional function. The assessments of uncertainties given above are thus interpreted as follows:
By studying the other data included in the calculations in the same way and carry out a computer simulation of uncertainties of a series of selected commodity groups, it is considered possible to achieve a realistic impression of the average uncertainties of the calculation results. It is emphasized that this way of assessing the uncertainties provides the impression of the average uncertainties rather than the maximum uncertainties, as in reality an equalizing of the uncertainties within a certain data type takes place. The ASC values, based on studies from literature and of a relatively low uncertainty, are affected by the high uncertainty of the ASC values based on enthalpy values etc. and vice versa. Thus the assessment method will not intercept the worst possible cases, which is here considered acceptable, as the aim is to achieve an assessment of the general sustainability of the calculation results (when should the ranking of two commodity groups be considered identical and different respectively) and not the definitive truth of each commodity group. For the computer simulation a special computer program "RISK", which is a superstructure of the spreadsheet program Excel, was applied. RISK has the property that a fixed value (a figure in a cell of the spreadsheet) is replaceable by a set of values, which fulfil a given statistical distributional function. In the present case each of the data included in the calculation of loss of resources and energy consumption will be replaced by a statistical distributional function. In other respects the programme functions in such a way that a considerable number of calculations of both loss of resources and energy consumption are carried out. Ateach calculation, a ransom figure, which is in accordance with the chosen statistical distributional function, will be generated for each data. After completed calculations the mean values, the frequency distribution and the standard deviations of the results were calculated. These uncertainty calculations were based on the calculated expressions of the loss of resources and the energy consumption respectively indicated in box 1.1. For quantity data it was taken into consideration that the calculations in reality are based on the mean value of production and supply, i.e. that actually two quantity data are included in the calculations - and not just one quantity data as is shown in box 1.1. For energy consumption for extraction, manufacture and processing of materials (EPX) it was correspondingly taken into consideration that this energy consumption is composed of ASC + processing supplement. The uncertainty of data types is basically defined as described above for the ASC values (i.e. as a step distribution). At the actual uncertainty calculations it was however chosen to replace the step distribution by a logarithmic normal distribution (lognormal). This choice was made, because a continuous distribution must be expected to reflect reality better than a step distribution. The logarithmic normal distribution is moreover characterised by its natural zero (data values cannot be negative) and by its behaviour like the normal distribution in connection with high data values. The conversion of step distribution to lognormal distribution was done by choosing a lognormal distribution, which is - based on the standard deviation - was the best possible approximation to the step distribution. All lognormal distributions used in the calculations were identified by the standard deviation (which was here assumed determined by the data type) and the mean value (which is the figure used in the ordinary calculation). The lognormal distribution for the ASC material "m050 Aluminium" was thus unambiguously determined as lognormal (190, 40) where 190 is the estimated ASC value of the material (cf. table 1.5) and 40 is the estimated standard deviation of the ASC values generally (cf. table 2.1). For each type of data included in the calculations table 2.1 shows partly the assumed step distribution of uncertainties and partly the lognormal distribution (identified by the standard deviation), which is assumed to correspond most accurately to the step distribution. The rationale behind assumed step distributions is described in the following: Quantity data According to information from Statistics Denmark /24/ quantity data for approx. 75% of all tariff numbers are available directly from Statistics Denmark, as data for production, imports and exports are reported in tonnes and not subject to confidentiality. These data are normally considered the best and thus in principle true. Empirically even those data will be uncertain because of statistical threshold values, use of incorrect tariff numbers, imprecise quantity data, inclusion of retail packaging in the net weight etc. No certain knowledge of the size of these errors is available - not with Statistics Denmark /24/ either. Here it was consequently assumed that the predominant part (approx. 90%, corresponding to approx. 65% of all tariff numbers) of these data holds a relatively modest uncertainty (5%), whereas a minor part (ca. 10%, corresponding to approx. 10% of all tariff numbers) is holding a significant uncertainty (50%). The remaining 25% of all tariff numbers includes the numbers for which it was necessary to estimate the quantity data by recalculation on the basis of the foreign trade statistics and the numbers subject to confidentiality or for which it was necessary to estimate the quantity data for some other reason. The tariff numbers, the quantities of which were found by calculation on the basis of the foreign trade statistics, include approx. 22% of all tariff numbers. The precise uncertainty of these data is not known, but is assumed to be 25%.The tariff numbers, of which the quantity data were estimated (3% of all numbers) were here conservatively assumed to hold an uncertainty of 100%. It was estimated here that the uncertainty was much lower in many cases, but a few data were deliberately estimated very conservatively. These uncertainty estimates were based on the uncertainty of the individual tariff numbers, thus disregarding an actual equalizing of the uncertainties taking place when the tariff numbers were collected in commodity groups. As this effect lacked clarity, the uncertainty of the tariff numbers was her chosen as the basis of the assessment. Correction factor The correction factor is uncertain because of uncertain estimates of the quantity of working means, spare parts and packaging compared to the weight of the industrial product; i.e. that at these points the uncertainty of the estimated material composition will affect the correction factor. The correction factor might also be misjudged because the quantity information includes packaging. This type of uncertainty was included in the quantity data, but not in the correction factor. An overall estimate is that working means and spare parts have only importance to approx. 20% of the total amount of commodity groups. For the cases in which the correction factor is limited to the importance of packaging, the correction factor will normally be modest (< 1.05) and the uncertainty consequently low (< 5%). For the remaining 20% of the commodity groups the uncertainty of the correction factor will be substantial to significant. It was assumed her that for 15% of the commodity groups the uncertainty was 20%, whereas it was estimated at 50% for the remaining 5%. Contents of material This concerns the contents of the individual material in the commodity group, i.e. the material composition. These contents are stated as a percentage value, which can be between 0 and 100. From the initiation of this project it was estimated that this percentage value was to be determined with an absolute uncertainty of 5%. This means that for a material, the contents of which is stated as 75%, the true value will be within the interval of 70 and 80%, whereas the true value of a material, the contents of which are stated as 5%, will be within the interval of 0 to 10%. This uncertainty reflects that the contents value of the dominant materials of a commodity group is fairly accurate, whereas the value of the materials of smaller shares is very uncertain. At the calculations it was secured that the sum of all contents values (except for water as a working means) is always 100. Loss of resources for materials Here it was determined that for all non-recyclable materials, thus with a loss of resources of 100%, this value was established with an uncertainty of 0%. This was the case for approx. 75% of all materials of the material list (cf. table 1.5). For the other materials it is estimated that the uncertainty generally is limited, but that some misjudgements might have happened for a few commodity groups. It was consequently estimated that 15% of the total estimates of loss of resources has an uncertainty of 20%, whereas the remaining 10% has an uncertainty of 100%. Reference is made to comments in the above text. Energy content It is assumed that for all materials, in which the energy content is 0 (applies to approx. 40% of all materials), this value was determined without any uncertainty. For the remaining materials it is assumed that the value because of many investigations is determined fairly precisely, but that for material groups consisting of many different materials the stated values might be considerably uncertain. Additionally, there are the situations in which the material list does not include a material corresponding precisely to the material in the commodity group. Here it was assumed that for 50% of all materials there is an uncertainty of 20%, whereas for the remaining 10% an uncertainty of 100% was assumed. Processing supplement For 80% of all materials no processing supplement was defined. For these materials it was assumed that the supplement was determined with the uncertainty of 0 (in these cases the uncertainty was in principle included in the ASC value). For materials, for which a processing supplement had been defined, it was estimated that the uncertainty of the size of this supplement is generally high. Here it was assumed that the processing supplement for 10% of all materials was determined with an uncertainty of 50%, whereas for the remaining 10% the uncertainty was 100%. Energy consumption during the life cycle Uncertainties of the estimates of the energy consumption during the life cycle are related to conditions as e.g.:
It is assessed that the estimates made are seldom completely correct, but seldom quite incorrect either. It cannot be excluded however that a few incidents of substantial misjudgements have taken place. Consequently it was assumed that for 80% of the estimates the uncertainty was 20%, for 15% of the estimates 50%, and for the remaining 5% the uncertainty was 100%. Average weight of products in the commodity group Estimates of the average weight of products in the commodity group are uncertain related to whether the products in question, on which the estimate is based, are a true average of all the products in the commodity group. This estimate is however in many cases based on information from the statistics (total number/total weight), which is assessed to hold a relatively low uncertainty. It was therefore assumed that80% of all estimates hold a relatively low uncertainty (10%), whereas the remaining 20% has an uncertainty of 50%. Share of waste that is combusted The precondition of the calculations was that on average 75% of all combustible waste in Denmark is taken to solid waste incineration plants. Seen in relation to the individual commodity groups this precondition must be considered uncertain. Even though the majority of the loss of resources in all probability will end up in solid waste incineration plants, it is far from certain that the share is precisely 75%. Furthermore, of the individual commodity groups (e.g. foodstuffs, feedstuff etc.) the predominant part of the loss of resources will be utilized in another way - and only to a very limited extent end up in solid waste incineration plants. It was consequently assumed that in 80% of all cases the precondition held an uncertainty of 20%, whereas in the remaining cases the uncertainty was 100%. Energy efficiency of solid waste incineration plants At the calculations an energy efficiency of 80% was assumed. This assumption will probably be almost correct in most cases, as the capacity of each incineration plant is adapted to the waste available, and by and large all incineration plants must expect that the waste-generated heating cannot be utilised in full during the summer period. The assumption is however also used for commodity groups such as pit coal, for which the energy efficiency is typically considerably lower. Here it is therefore considered correct to assess that in 80% of all cases the assumption holds an uncertainty of 20%, whereas the remaining cases hold an uncertainty of 50%. Results The results of the uncertainty calculation appear from table 2.2. Besides the calculated mean values of the loss of resources and the energy consumption the table shows also the standard deviation of the calculation results and the interval, within which 90% of all the results is. Energy consumption As it appears from the results of the energy consumption, the interval - within which 90% of the results are - is typically within the range of -50 to +76% of the mean value. This result is to be interpreted in such a way that all the results of energy consumption stated in appendix 1 should be considered an interval determined by the result -50% and +76% respectively. Intervals, which do not overlap each other, represent in all probability energy consumption values that are in reality different. Contrary to that, intervals that to a greater or smaller extent overlap each other represent energy consumption values, which are almost likely to be identical. On the basis of the ranking result of the energy consumption in appendix 1 it can for example be estimated
Loss of resources For loss of resources the results were characterized by large deviations. It is clear however that the commodity groups, the results of which hold a high uncertainty, are all characterised by being composed of renewable materials, which are recreated concurrently with their use. The loss of resources, which is calculated, forms therefore only the modest part of the materials of the commodity group that is non-renewable, that is to say packaging, printing ink and the like. It should be no matter for surprise that the uncertainty of the loss of resources of such commodity groups is generally characterised by the fact that the dominant materials were determined with a low uncertainty, whereas the marginal materials were decided with high uncertainty. This uncertainty was incorporated in the assessment method applied in this project (cf. section 1.4 Threshold values). For commodity groups, consisting predominantly of renewable materials it was concluded that the uncertainty of the loss of resources can be so significant that establishing general criteria for it makes no sense. In practice the result must be assessed in detail in each individual case. For commodity groups, which have some share of non-renewable materials, it was assessed meaningful to talk of a typical uncertainty. Parallel to the assessments of energy consumption it was - based on the results in table 2.2 - assessed that the interval - within which 90% of the results are - is typically of the size of -42 to +61% of the mean value, meaning that all results of loss of resources stated in appendix 1 should be considered an interval determined by the result -42% and +61% respectively. With this as a starting point and based on the ranking results of loss of resources in appendix 1 the following assessments can be made:
These uncertainty considerations show that even though the calculation results hold uncertainty and thus correspondingly also the ranking of the different commodity groups in relation to each other, the stated ranking will nevertheless could be used as a clear indication of the attention that should be given to the various commodity groups. Except for the commodity groups that predominantly consist of renewable materials, and in connection with which the loss of resources must be estimated in detail in each individual case, it is beyond doubt that the commodity groups with high ranking on the list are the groups resulting in the most significant loss of resources and energy consumption. 2.3 Overall assessmentRanking The ranking of industrial products carried out in this project shows that the properties of industrial products that will typically indicate that products have a large loss of resources and/or energy consumption and thus have a high ranking, are the following:
It is hardly surprising that especially the industrial products appearing at the top of the ranking list are products and goods related to the energy sector, transport sector, agriculture and building and civil sectors. Especially the sectors energy, agriculture and building/civil are characterised by the fact that substantial quantities of quite few articles are consumed/manufactured. Contrary to that, means of transport, such as ships, trains and cars, are characterised by a very large consumption of energy as well as working means (lubricating oil, tyres etc.) during use. For comparison the production and consumption within other sectors are distributed on many different articles, meaning that individually they do not carry great weight in the total accounts. There are however also a series of consumer goods competing for high ranking on the list. These are typically products requiring energy or working means during use, such as refrigerators and freezers, washing machines, television and lighting accessories - or products sold in very large quantities, such as furniture, beer, papers and magazines. A series of commodity group topping the ranking list must incidentally be considered semi-manufactures rather than finished goods. This applies to e.g. goods like pit coal, oil, natural gas, diesel motors, feedstuffs, cement and packing articles. This does not mean however that they are uninteresting. An example is that the efficiency of engines in reality has decisive importance for the energy consumption of means of transport. Especially interesting are commodity groups like machines for textile processing, vending machines and casting machines, which are high-ranking because of the large consumption of working means (chemicals, disposable drinking cups, moulding sand) besides energy consumption throughout the entire life cycle. It should be stressed that the ranking made here does not consider the utility value of the industrial products in the community or the contents of environmentally harmful substances etc. Thus it does in no way mean that a product is especially "poor or environmentally harmful", if it is at the top of the list. That a product is ranked at the top of the list means however in actual fact that a very large loss of resources and/or energy consumption are connected to it. It might therefore be in the interest of the community to assess possible improvements/changes/consumption reductions etc. that should be initiated for this specific product. The interest of the community in initiating improvements is not necessarily limited to the products ranked at the top. It might be relevant to focus on products ranked further down the list, e.g. motivated by the contents of environmentally harmful substances, pollution during the phase of production etc. Method It is assessed that the method for ranking of industrial products applied in this project has proved useful for the purpose. The main basis for this assessment is that the result achieved (the ranking) must be considered logical and well-founded. When this has been said, it must be recognized though that the method as well as the data in many ways could and should be improved. Neither the commodity group division nor the collected data of commodity groups and materials can be considered optimal and impeccable. The calculation of the energy quantity that can be reclaimed from the loss of resources is not optimal either. Uncertainties This means as assessed in section 2.2 that all calculation results including the ranking are naturally uncertain. These uncertainties imply that it makes no sense to assert that the commodity group ranked as no. 30 is more environmentally harmful than the commodity group ranked as no. 35, or to emphasize no 250 in preference to no. 300. Contrary to that, it makes sense to consider the commodity groups ranked as no. 1 to approx. 50 as having more environmental impact than the commodity groups ranked as no. 100 to 200 etc. As it appears, the focus should be on the general lines. Besides the uncertainties pointed out in section 2.2, the uncertainty related to the division of industrial products into commodity groups should also be stressed. The larger quantities a commodity group includes, the higher it will be ranked. Splitting up a commodity group into more groups is consequently an efficient way of reducing the importance of certain industrial products in a ranking system like this. In this project it was deliberately attempted to minimise the amount of commodity groups, thus gathering various industrial products in the same group to the extent considered at all appropriate. It is obvious that the division can always be discussed, and that some of the choices made after careful consideration will turn out to be wrong. Accumulation of knowledge It is assessed that the knowledge of industrial products and materials achieved during this project - all uncertainties considered - has enabled an identification of the types of industrial products to which the focus should be directed in the future environmental efforts, as well as it will be available for utilisation in other connections as described in the following section. During this project an actual accumulation of knowledge within the field of products and materials took place. It should be emphasized that the knowledge presented in this main report including appendices 1a and 1b could be considered the top of the iceberg, when compared to the knowledge available in the database and the other appendices. |
