www.jard.edu.pl DOI: 10.17306/ Journal of Agrbusness and Rural Development pissn 1899-5241 eissn 1899-5772 2(40) 2016, 345 354 WASTE MANAGEMENT IN POLAND (2012 2013) SPATIAL ANALYSIS Karol Kukuła Unwersytet Rolnczy m. Hugona Kołłątaja w Krakowe Abstract. The condton of the waste management development s a complex phenomenon descrbed by eght dagnostc varables. The purpose of the paper s to ndcate regonal dscrepances n the scope of shapng of the phenomenon n 2012 and 2013. To acheve the purpose, the multvarate analyss was appled, wth a partcular focus on the zero untarzaton method. As a result of applcaton of the aforementoned methods, the rankng of vovodeshps wth respect to the level of ther waste management development was obtaned. Further, the vovodeshps were dvded nto four groups: at a very hgh, hgh, moderate, and low level of the waste management development. The level of the waste management development s not evenly dstrbuted between gven vovodeshps. There are sgnfcant dscrepances wthn the nvestgated area between the vovodeshps leadng n the rankng (Mazowecke), and the last vovodeshp n the fourth group (Śwętokrzyske) [I(Q ) 52.5 n 2013]. Key words: waste, vovodeshp, dagnostc varable, object, rankng INTRODUCTION Waste management s a sgnfcant element of boeconomy. Sgnfcant waste-related tasks lyng ahead of the humanty nclude waste collecton, separaton, converson of waste to energy and heat, or resources for further processng, and waste treatment. Socetes world-wde face challenges related, on the one hand, to the onerousness and harmfulness of excessve waste supples and the abltes to process waste nto goods for people, on the other. The paper attempts to evaluate the level of the waste management development n gven vovodeshps n Poland. The research was carred out n two subsequent years: 2012 and 2013. It allows conductng the comparatve analyss of the level of changes n 2013 wth respect to the prevous year. The evaluaton of the level of the waste management development requres takng several determnants nto consderaton. In other words, the category condton of the waste management development s a complex one (Kukuła, 2000) n contrast to smple phenomena descrbed wth one varable. The followng task was to determne the lst of varables characterzng the level of the waste management development n Poland. The fnal result of the research s the rankng of vovodeshps (objects) wth respect to the value of a synthetc varable,.e. the condton of the waste management development. In the next step, all objects were dvded nto four groups: at a very hgh, hgh, moderate, and low level of development of the nvestgated phenomena. Wth respect to the fact that both 2012 and 2013 vovodeshp rankngs were known, spatal changes were evaluated n the scope of the waste management development whch occurred at the nvestgated perod of tme. Reuse of waste translates nto measurable economc benefts. It creates opportuntes for economc development of regons by management of agrcultural and nonagrcultural post-producton waste resultng n new jobs for people (see Skorwder-Namotko, 2015). prof. dr hab. Karol Kukuła, Katedra Statystyk Ekonometr, Wydzał Rolnczo-Ekonomczny, Unwersytet Rolnczy w Krakowe, al. Mckewcza 21, 31-120 Kraków, Poland, e-mal:ksm@ur.krakow.pl Copyrght by Wydawnctwo Unwersytetu Przyrodnczego w Poznanu
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ The subject to the present research s the level of the waste management development n Poland n 2012 and 2013, a complex phenomenon descrbed by several varables. The collected data on dagnostc varables characterzng the level of a complex phenomenon create a matrx: x11 x21 X xr1 x x x 12 22 r 2 x1 n x 2n, xrn 1,..., r, (1) j 1,..., n where r s the number of objects (vovodeshps n ths case), and n n the number of dagnostc varables. Therefore, x j s the value of a varable X j n an th object. Data on the selected dagnostc varables were taken from the followng GUS annual sets (GUS, 2013; 2014). RESEARCH METHOD The selecton of dagnostc features s a dffcult and extremely mportant task affectng fnal results. When creatng a rankng of vovodeshps wth respect to the level of a complex phenomenon,.e. the condton of the waste management development, one appled two crtera: mert and statstcal ones. The statstcal crteron s an adequate level of varaton of the feature prevously qualfed due to the mert crteron. To specfy the varaton level one appled a smple measurng tool,.e. the quotent of extreme values of each varable (X 1,, X n ): max xj I( Xj) (2) mn xj Moreover, t s assumed that a feature fully correspondng to the mert crtera has to fulfl the followng condton: I(X j ) > 2 (3) If a feature X j takes fxed values, then I(X j ) = 1. The ncrease n the measurng tool means growng dscrepances (dfferences) between the best and the worst objects n relaton to a gven dagnostc varable. The measurng tool (2) consttutes suffcent crteron to determne an adequate level of varaton of a feature qualfed to the set of dagnostc varables for the major purpose of the present research,.e. preparaton of the rankng wth respect to the level of the nvestgated complex phenomenon. The multvarate comparatve analyss covered the dvson of dagnostc features nto stmulants and destmulants, ntroduced for the frst tme n the Polsh lterature of the subject by Z. Hellwg (1968). Constructng of synthetc varables should be preceded by transformaton of dagnostc features, the so-called normalzaton. Ths process transforms varous values of features of dagnostc values n ther orgnal shape nto comparable ranges and reduces ther denomnaton. The normalzaton method appled n the research to transform a feature X j nto a varable Z j s called the zero untarzaton method, descrbed n detals n (Kukuła, 2000). The dagnostc varables appled n the present research are stmulants,.e. such varables whose ncrease reflects the ncrease n the evaluaton of a complex phenomenon. Therefore, the formula appled to transform a feature X j nto a varable Z j s the followng: xj mn xj zj (4) max xj mn xj Values of the normalzed dagnostc features z j fulfl the followng relaton: z j [0,1] (5) Relatons between extreme values of the features n ther orgnal shape and the transformed features are expressed n the followng way: and z j z j j 0 x mn x (6) j j 1 x max x, (when X j s a stmulant) (7) Values z j form a lnear transformaton of the dagnostc varables-stmulants x j n ther orgnal shape. Normalzed values of the dagnostc features wth the formula (4) can be presented n the form of a matrx: z11 z12 z1 n z21 z22 z2n 1,..., r Z,. (8) j 1,..., n zr1 zr 2 zrn The matrx (8) consttutes the bass of aggregaton of the normalzed features, and at the same tme, gves a synthetc varable Q characterzng the level of a complex phenomenon n every object r: 1 Q n z j n j1 j (9) 346 www.jard.edu.pl
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Synthetc varables obtaned by means of the formula (9) take the values from the range [0, 1]. One should also add that: Q 1 z 1 z2... zn 1 (10) and Q 0 z 1 z2... zn 0 (11) Such extremes are rarely encountered n emprcal studes on complex phenomena. Therefore, all nvestgated objects are characterzed by the vector: Q1 Q2 Q, (12) Q r whch allows constructng a rankng of objects wth respect to the level of development of the nvestgated phenomenon. A rankng means an ordered set of objects where objects of the hghest values of a feature Q take frst postons, and an object wth the lowest value of a synthetc varable Q takes the last poston. Another step n the research s to dvde objects nto a gven number groups. Due to the number of objects subject to the research (16 vovodeshps) t seemed reasonable to dstngush three groups by means of the followng algorthm (Kukuła, 2014): a) calculate a range for a synthetc varable: R( Q ) maxq mn Q (13) b) determne a value of a dvson parameter k accordng to the formula: 1 k R( Q ) (14) 3 c) dvde objects nto groups n the followng way: group I at a hgh level of development of the nvestgated phenomenon Q [ maxq k,maxq ] (15) group II at a moderate level of development of the nvestgated phenomenon Q [ maxq 2k,maxQ k) (15) group III at a low level of development of the nvestgated phenomenon Q [ maxq 3k,maxQ 2k). (15) If more than one rankng appears n studes (for example, n the present research there are two rankngs of the same phenomenon for two dfferent perods of tme (t = 0 and t = 1)), the followng formula can be appled for the comparson of dscrepances between both rankngs U 0 and U 1 (Kukuła, 1986): r 2 dj 1,..., r 1 m, 01, (16) 2 r z j 1,..., n where d j = c 0 c 1 (17) 0 f r P and z, (18) 1 f r P where: c 0 poston of an th object n the rankng for the perod t = 0 c 1 poston of an th object n the rankng for the perod t = 1 P set of even natural numbers. The measurng tool m 01 takes values from the range [0, 1]. The value of the measurng tool equal to 0 refers to the stuaton when the rankng for t = 1 s dentcal as the rankng for t = 0. And the other way around, m 01 = 1 means maxmum dversty between both rankngs. Lets consder two order sets: U 0 = [B, A, D, C, F, G, E] and U 1 = [E, G, F, C, D, A, B]. In such stuaton, the measurng tool m 01 s equal to 1. Frst letters of the alphabet denote objects wth respect to postons they take n rankngs U 1 and U 0. SELECTED DIAGNOSTIC VARIABLES Wth respect to the aforementoned selecton crtera, one dstngushed eght dagnostc varables characterzng the level of the waste management development n the subsequent years: 2012 and 2013. The varables are lsted below: X 1 the volume of muncpalty waste collected and treated n kg per nhabtant X 2 the number of controlled waste landfll stes X 3 the number of landfll stes wth degassng systems X 4 the number of landfll stes wth degassng systems and energy recovery X 5 recyclng of glass packagng waste n thou. tons www.jard.edu.pl 347
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Table 1. Values of dagnostc varables descrbng the level of waste management n Poland n 2013 Tabela 1. Wartośc zmennych dagnostycznych opsujących stopeń rozwoju gospodark odpadam w Polsce w 2013 roku Vovodeshps Województwa X 1 X 2 X 3 X 4 X 5 X 6 X 7 X 8 Dolnośląske 261,1 30 29 4 24 577 69 931 6 561 94 Kujawsko-Pomorske 211,2 32 21 4 2 530 27 556 6 829 73 Lubelske 140,3 56 40 1 0 2 673 161 45 Lubuske 268,1 14 11 1 49 5 358 1 362 39 Łódzke 199,1 23 22 4 0 1 178 1 417 75 Małopolske 176,5 23 23 5 137 784 92 992 28 209 110 Mazowecke 214,3 57 45 10 274 747 478 037 116 240 194 Opolske 214,5 21 20 1 0 10 540 867 32 Podkarpacke 142,6 22 18 2 7 827 2 560 1 825 54 Podlaske 195,0 15 11 1 0 44 351 18 Pomorske 245,2 18 17 4 932 26 897 4 314 83 Śląske 252,2 26 24 11 0 6 401 1 895 186 Śwętokrzyske 111,7 15 13 1 0 1 008 701 28 Warmńsko-Mazurske 205,4 19 11 1 25 3 603 979 48 Welkopolske 236,0 43 41 4 14 070 15 439 3 015 133 Zachodnopomorske 264,7 17 17 5 3 286 33 903 4 172 64 I (X j ) 2,40 4,07 4,09 11,00 10 989,88* 10 864,48 721,99 10,78 Polska Poland 212,9 431 363 59 465 827 778 120 178 898 1 275 *In the case of varable X 5 you shouldn t calculate value of I(X 5 ) because dvdng by 0 s mpossble. Therefore you have to take mnmum of the remanng values of ths varable. Source: GUS, 2014. *W przypadku zmennej X 5 ne można przy lczenu I(X 5 ) dzelć przez 0, wzęto zatem mnmum z pozostałych wartośc tej zmennej. Źródło: GUS, 2014. X 6 recyclng of paper and cardboard packagng waste n thou. tons X 7 recyclng of plastc packagng waste n thou. tons X 8 the volume of waste collected and separated n thou. tons. Table 1 presents the data on the dagnostc varables collected n 2013 (X 1, X 2,, X 8 ). Ther normalzed values are shown n Table 2. When analysng the values of the measurng tool I(X j ) for all selected dagnostc varables, what draws partcular attenton s the large scale of varaton of features X 5, X 6 and X 7 (see Table 1). All these features are related to recyclng of packagng waste of glass, paper and cardboard, and plastcs. Recyclng s a type of recovery where waste s processed nto products, materals, or substances for reuse. Therefore, recyclng should be treated as a manfestaton of nnovaton n economy. As far as recyclng of the aforementoned waste s concerned, two vovodeshps are evdent leaders n ths area n Poland: Mazowecke and Małopolske (Table 1). Ths s to some extent reflected n the rankngs constructed both for 2013 and 2012 (Table 3 and 4). 348 www.jard.edu.pl
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Table 2. Values of dagnostc varables descrbng the level of waste management n Poland n 2013 Tabela 2. Wartośc unormowanych zmennych dagnostycznych opsujących stopeń rozwoju gospodark odpadam w Polsce w 2013 roku Vovodeshps Województwa Z 1 Z 2 Z 3 Z 4 Z 5 Z 6 Z 7 Z 8 Σz j Q Dolnośląske 0.955 0.372 0.529 0.300 0.089 0.146 0.055 0.432 2.878 0.3598 Kujawsko-Pomorske 0.636 0.419 0.294 0.300 0.009 0.058 0.057 0.313 2.086 0.2607 Lubelske 0.183 0.977 0.853 0 0 0.006 0 0.153 2.172 0.2715 Lubuske 1.000 0 0 0 0.001 0.011 0.010 0.119 1.141 0.1426 Łódzke 0.559 0.209 0.324 0.300 0 0.002 0.011 0.324 1.729 0.2161 Małopolske 0.414 0.209 0.353 0.400 0.103 0.194 0.242 0.523 2.438 0.3048 Mazowecke 0.656 1.000 1.000 0.900 1.000 1.000 1.000 1.000 7.556 0.9445 Opolske 0.657 0.163 0.265 0 0 0.022 0.006 0.080 1.193 0.1491 Podkarpacke 0.198 0.186 0.206 0.100 0.028 0.005 0.014 0.205 0.942 0.1178 Podlaske 0.533 0.023 0 0 0 0 0.002 0 0.558 0.0698 Pomorske 0.854 0.093 0.176 0.300 0.003 0.056 0.036 0.369 1.887 0.2359 Śląske 0.898 0.279 0.382 1.000 0 0.013 0.015 0.955 3.542 0.4428 Śwętokrzyske 0 0.023 0.059 0 0 0.002 0.005 0.057 0.146 0.0183 Warmńsko-Mazurske 0.599 0.116 0 0 0.001 0.007 0.007 0.170 0.900 0.1125 Welkopolske 0.795 0.674 0.882 0.300 0.051 0.032 0.025 0.653 3.412 0.4265 Zachodnopomorske 0.978 0.070 0.176 0.400 0.012 0.071 0.035 0.261 2.003 0.2504 Source: own elaboraton on the bass of data from Table 1. Źródło: oblczena własne na podstawe danych z tabel 1. EMPIRICAL RESEARCH RESULTS IN 2013 By means of the avalable data presented n Table 2 and the formula (9) the rankng of vovodeshps was constructed concernng the level of the waste management development n Poland n 2013. The rankng s shown n Table 3. The unquestonable leader of the rankng wth an edge over other regons s Mazowecke; ts synthetc varable (0.9445) s twce as hgh as the synthetc varable for śląske (0.4428) whch was on the second poston n the rankng. It should be noted that the rankng demonstrated sgnfcant dscrepancy n the value of a synthetc varable I(Q ) 52.5. It means that, as far as the waste management development s concerned, mazowecke outrvaled Śwętokrzyske, the last vovodeshp n the rankng, over 52 tmes. Applyng the procedure determned n the formulas (13), (14), and (15), the objects from the 2013 rankng were dvded nto 3 groups, as prevously assumed. Due to the outler (Mazowecke) an empty group between ths vovodeshp and the rest of the objects was obtaned. Therefore, the dvson procedure was repeated wth excluson of Mazowecke. Ths vovodeshp consttutes a separate, ndvdual group at a very hgh level of development of the nvestgated phenomenon. Another group II at a hgh level of the waste management development covers four vovodeshps (n the exact order: Śląske, Welkopolske, Dolnośląske, and Małopolske). Group III at a moderate level of development of the phenomenon subject to the research ncludes fves vovodeshps, n the followng order: Lubelske, Kujawsko-Pomorske, Zachodnopomorske, Pomorske, and www.jard.edu.pl 349
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Table 3. Rankng of vovodeshps accordng to the level of waste management n 2013 Tabela 3. Rankng województw według stopna rozwoju gospodark odpadam w 2013 roku Place n rankng Pozycja w rankngu Vovodeshps Województwa Q 1 Groups (wth number of vovodeshps) Grupy (z lczbą województw) 1 Mazowecke 0.945 I (1) 2 Śląske 0.443 3 Welkopolske 0.427 4 Dolnośląske 0.360 5 Małopolske 0.305 6 Lubelske 0.272 7 Kujawsko-Pomorske 0.261 8 Zachodnopomorske 0.250 9 Pomorske 0.236 10 Łódzke 0.216 11 Opolske 0.149 II (4) III (5) 12 Lubuske 0.143 13 Podkarpacke 0.118 14 Warmńsko-Mazurske 0.113 IV (6) 15 Podlaske 0.070 16 Śwętokrzyske 0.018 I(Q 1 ) 52.5 Source: own elaboraton on the bass of data from Table 2. Źródło: oblczena własne na podstawe danych z tabel 2. Łódzke. The last group IV conssts of 6 vovodeshps: Opolske, Lubuske, Podkarpacke, Warmńsko-Mazurske, Podlaske, and Śwętokrzyske. Fgure 1 presents the spatal dstrbuton of the groups. EMPIRICAL RESEARCH RESULTS IN 2012 By constructng the second rankng of vovodeshps wth respect to the same complex phenomenon n 2012 one amed at obtanng a bass for comparson of the results for 2013. The paper used the data from the earler paper by (Kukuła, 2014) coverng the rankng of vovodeshps wth respect to the waste management development n Poland n 2012. Therefore, to obtan a specfc pont of reference, the rankng of vovodeshps (Table 4) and ther spatal dstrbuton were presented n Fgure 2. Only Mazowecke belongs to group I at the hghest level of development of the phenomenon subject to the research. The last group IV ncludes the same 6 vovodeshps as group IV n the rankng for 2013, wth only small, ntra-group dslocatons. It should be hghlghted that ths group s the largest group n both rankngs for 2012 and 2013. COMPARISON BETWEEN RANKINGS 2013/2012 The result of comparng both rankngs on the condton of the waste management development n 2012 and 2013 determnes the level of changes n the orders for the nvestgated area. To specfy the level of these changes n a quanttatve way, one should apply the 350 www.jard.edu.pl
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Pomorske Podlaske Ma Lubuske Welkopolske Opolske Lubelske Fg. 1. Vovodeshps accordng to the level of waste management n 2013 Source: own elaboraton on the bass of data n Table 3. Rys. 1. Województwa wg stopna rozwoju gospodark odpadam w 2013 roku Źródło: opracowane własne na podstawe danych z tabel 3. Podkarpacke Q 0,945 Q [0,301; 0,443] Q [0,160; 0,301) Q [0,018; 0,160) Pomorske - Zachodnopomorske Kujawskopomorske - Zachodnopomorske Kujawskopomorske Podlaske Ma Fg. 2. Vovodeshps accordng to the level of waste management n 2012 Source: Kukuła, 2014. Ryc. 2. Województwa wg stopna rozwoju gospodark odpadam w 2012 roku Źródło: Kukuła, 2014. Lubuske Welkopolske Lubelske Opolske Podkarpacke Q 0,920 Q Q Q [0,292; [0,143; [0,005; 0,435] 0,292) 0,143) www.jard.edu.pl 351
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Table 4. Rankng of vovodeshps accordng to the level of waste management n 2012 Tabela 4. Rankng województw wg stopna rozwoju gospodark odpadam w 2012 roku Place n rankng Pozycja w rankngu Vovodeshps Województwa Q 0 Groups (wth number of vovodeshps) Grupy (z lczbą województw) 1 Mazowecke 0.920 I (1) 2 Welkopolske 0.435 3 Śląske 0.421 4 Dolnośląske 0.385 5 Małopolske 0.376 6 Kujawsko-Pomorske 0.314 7 Zachodnopomorske 0.312 8 Pomorske 0.275 9 Lubelske 0.243 10 Łódzke 0.207 11 Opolske 0.147 12 Lubuske 0.136 13 Podkarpacke 0.113 14 Podlaske 0.107 15 Warmńsko-Mazurske 0.098 16 Śwętokrzyske 0.005 I(Q 0 ) 184.0 Source: Kukuła, 2014. Źródło: Kukuła, 2014. II (6) III (3) IV (6) measurement (16). The measurement takes values from the range [0, 1], and s dstrbuted n a lnear way for all changes between postons of the objects n both perods of tme subject to comparson. The varaton range for the measurement allows nterpretng by means of a percentage scale. To determne the value of the nter-rankng comparson measurement, one prepared Table 5. After adequate substtutons n formulas (16) and (17), the followng formula was obtaned: 2 10 20 m 1 0.078 (19) o 2 16 0 256 The result means slght changes n the nvestgated rankngs n the compared perods of tme. The level of dscrepancy for both orders can be determned as the change at the level of around 8%. In other words, vovodeshps postoned at top ranks n the 2012 rankng took the same hgh postons n 2013 wth slght changes, and all vovodeshps n the last group of the lowest waste management development level stayed n the same group n 2013. In both rankngs mazowecke was the leader clearly outrvalng the vovodeshp on the second place. When analysng the value of a synthetc varable, t s vsble that the vovodeshp ncreases ts dstance to the second object n the rankng. The same stuaton s observed for the last poston. Śwętokrzyske s the last one n both rankngs. Takng nto account also the postve sdes of the evaluaton, one should add that the vovodeshp slghtly mproved ts value of the synthetc varable from 0.005 to 0.018. However, t was not suffcent enough to go up n the rankng. 352 www.jard.edu.pl
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ Table 5. Postons of vovodeshps n rankngs n 2012 and 2013 Tabela 5. Pozycje województw w rankngach z lat 2012 2013 Current number Lp. Vovodeshps Województwa Rankng poston Pozycja w rankngu q 0 q 1 d d 1 Dolnośląske 4 4 0 0 2 Kujawsko-Pomorske 6 7 1 1 3 Lubelske 9 6 3 3 4 Lubuske 12 12 0 0 5 Łódzke 10 10 0 0 6 Małopolske 5 5 0 0 7 Mazowecke 1 1 0 0 8 Opolske 11 11 0 0 9 Podkarpacke 13 13 0 0 10 Podlaske 14 15 1 1 11 Pomorske 8 9 1 1 12 Śląske 3 2 1 1 13 Śwętokrzyske 16 16 0 0 14 Warmńsko-Mazurske 15 14 1 1 15 Welkopolske 2 3 1 1 16 Zachodnopomorske 7 8 1 1 Σ 0 10 Source: own elaboraton on the bass of data n Tables 3 and 4. Źródło: opracowane własne na podstawe tabel 3 4. CONCLUSION 1. The applcaton of the multvarate statstcal analyss s a useful tool n regonal studes. 2. Sgnfcant regonal dscrepances wth respect to the level of the waste management development for both of the nvestgated perods of tme were observed. 3. The vovodeshp at the hghest level of the waste management development n both perods of tme subject to comparson was Mazowecke. Its advantage n the synthetc varable value over other vovodeshps s very clear. Smlarly, Śwętokrzyske demonstrates the lowest level of the waste management development, vsbly outrvaled by other objects n group IV. 4. Group IV stays the same n both rankngs and ncludes the largest number of objects sx vovodeshps. 5. Takng nto consderaton the waste recyclng processes, one notced the clear advantage of two objects: Mazowecke and Małopolske over the other vovodeshps. 6. In the nvestgated perod of tme, slght, even mnute, changes n the ordnal dstrbuton of vovodeshps were observed (m 01 0.078). The complete stablzaton of the composton of group IV (the weakest objects) can trgger some anxetes. It means that vovodeshps at a low level of the waste management development do not undertake effectve efforts to leave the group. 7. Only fve objects represent a very hgh or hgh level of the waste management development n 2013; www.jard.edu.pl 353
Kukuła, K. (2016). Waste management n Poland (2012 2013) spatal analyss. J. Agrbus. Rural Dev., 2(40), 345 354. DOI: 10.17306/ they are as follows: (n the exact order) Mazowecke, Śląske, Welkopolske, Dolnośląske, and Małopolske. 8. Waste management s connected wth numerous felds such as: bo-economy, envronmental protecton, envronmental frendly actvtes, and acquston of renewable energy. REFERENCES GUS (2013). Ochrona Środowska Envronment 2013. Warszawa: GUS. GUS (2014). Ochrona Środowska Envronment 2014. Warszawa: GUS. Hellwg, Z. (1968). Zastosowane metody taksonomcznej do typologcznego podzału krajów ze względu na pozom ch rozwoju and zasoby and strukturę wykwalfkowanych kadr. Przegl. Stat., 4. Kukuła, K. (1986). Propozycja mary zgodnośc układów porządkowych. Zesz. Nauk. AE Krak. Kukuła, K. (2000). Metoda untaryzacj zerowanej. Warszawa: Wyd. Nauk. PWN. Kukuła, K. (2014). Regonalne zróżncowane stopna zaneczyszczena środowska w Polsce a gospodarka odpadam. Przeds. Zarz., XV, 8, I. Skorwder-Namotko, J. (2015). Pozom rozwoju bogospodark w Polsce w ujęcu regonalnym próba pomaru. Stud. Ekon. Reg., 8, 1. GOSPODARKA ODPADAMI W POLSCE (2012 2013) STUDIUM PRZESTRZENNE Streszczene. Stan rozwoju gospodark odpadam to złożone zjawsko, opsywane przez osem zmennych dagnostycznych. Celem artykułu jest wykazane zróżncowań regonalnych w zakrese kształtowana sę tego zjawska w latach 2012 2013. Dla realzacj tego celu wykorzystano metody welowymarowej analzy statystycznej, ze szczególnym uwzględnenem metody untaryzacj zerowanej. W wynku zastosowana opsanych metod otrzymano rankng województw ze względu na pozom rozwoju gospodark odpadam. W dalszej kolejnośc dokonano podzału województw na cztery grupy: bardzo wysokego, wysokego, przecętnego nskego pozomu omawanego zjawska. Pozom rozwoju gospodark odpadam ne rozkłada sę równomerne na poszczególne województwa. Istneją ogromne różnce w tym zakrese mędzy województwem przodującym w rankngu (mazowecke) a województwem ostatnm z czwartej grupy (śwętokrzyske): I(Q ) 52,5 w 2013 roku. Słowa kluczowe: odpady, województwo, cechy dagnostyczne, obekt, rankng Accepted for prnt Zaakceptowano do druku: 31.03.2016 354 www.jard.edu.pl