The Field Analysis: WEEE Collection Targets
WEEE Collection State
The
WEEE collected in Europe is measured through the kg of WEEE pro capite
(kgpc) which is the index adopted by the European Union as the target of
the collection efficacy. The target was 4 kgpc per year until 2015
(Directive 2002/96/EU, art. 5). Then, the new Directive (2012/19/EU) has
introduced stricter measures that correspond to a target of
about8kgpcfrom 2016 and about 10 kgpc from 2019.
As described in
Section 4, to set up the probability transition matrix, we have defined
three states based on the value of the kgpc of WEEE collected: low
(LWC), medium (MWC) and high (HWC). Considered that the HWC state
contains several provinces, it was further divided into three secondary
states: H1WC, H2WC and H3WC (Table 3).
Table 3. Summary of state about WEEE performance.
State. |
Range of WEEE kgpc |
LWC |
0–2 |
MWC |
2–4 |
HWC |
>4 |
-H1WC |
4–6 |
-H2WC |
6–8 |
-H3WC |
≥8 |
Descriptive Results
Table
4 reports the percentage of Italian provinces according to the first
three defined states (LWC, MWC, HWC) of WEEE collection statistics by
macro areas for the period 2008–2017. The HWC state (mainly related to
Northern provinces) ranges from 5.1 to 12.1 kg.
Table 4. WEEE statistics by collection states, macro-area and years (2008–2017): % of provinces.
|
Years |
|
2008 |
2009 |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
LWC (%) |
North |
28.2 |
1.8 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
Central |
20.0 |
5.5 |
2.7 |
2.7 |
2.7 |
0.9 |
1.8 |
1.8 |
0.9 |
0.9 |
South |
31.8 |
23.6 |
13.6 |
10.9 |
9.1 |
13.6 |
16.4 |
14.5 |
10.0 |
11.8 |
Italy |
80.0 |
30.9 |
16.4 |
13.6 |
11.8 |
14.5 |
18.2 |
16.4 |
10.9 |
12.7 |
MWC (%) |
North |
13.6 |
13.6 |
1.8 |
0 |
5.5 |
8.2 |
4.5 |
1.8 |
1.8 |
0.9 |
Central |
3.6 |
10.9 |
10.0 |
7.3 |
5.5 |
10.0 |
10.9 |
7.3 |
5.5 |
5.5 |
South |
1.8 |
6.4 |
12.7 |
13.6 |
17.3 |
13.6 |
10.9 |
10.9 |
12.7 |
10.9 |
Italy |
19.1 |
30.9 |
24.5 |
20.9 |
28.2 |
31.8 |
26.4 |
20.0 |
20.0 |
17.3 |
HWC (%) |
North |
0.9 |
27.3 |
40.9 |
42.7 |
37.3 |
34.5 |
38.2 |
40.9 |
40.9 |
41.8 |
Central |
0 |
7.3 |
10.9 |
13.6 |
15.5 |
12.7 |
10.9 |
14.5 |
17.3 |
17.3 |
South |
0 |
3.6 |
7.3 |
9.1 |
7.3 |
6.4 |
6.4 |
8.2 |
10.9 |
10.9 |
Italy |
0.9 |
38.2 |
59.1 |
65.5 |
60.0 |
53.6 |
55.5 |
63.6 |
69.1 |
70.0 |
From
a general point of view, we can observe that ten years after the
introduction of the WEEE regulation system, 70% of provinces shows a
relevant collection performance being in the HWC state (kgpc ≥ 4). Only
17.3% and 10.9% of these provinces are respectively in Southern and
Central Italy. Consistently, the percentage of provinces in LMC and MWC
states at the end of the period is low and mainly concentrated in the
South and Central area. Moreover, Northern provinces progressively moved
both from LWC (2008 = 28.2; 2017 = 0) and MWC (2008 = 13.6; 2017 = 0.9)
states state (2008 = 0.9; 2017 = 41.8).
It is worth highlighting the
huge growth in the HWC state in the first four years of the period
(2008–2011), whereas North, Central and South provinces increase
respectively of41.8, 13.6, and 9.1. In particular, by observing the
trend of the HWC state, it is worth highlighting the presence of two
different dynamics for the three territorial areas. In fact, a first
increase is visible for the period 2008–2012, then, after a slight
decline, a new increase is registered in the period 2014–2017. Probably
the first increase is derived from the impact of the digital switchover,
which involved the replacement of televisions sets and the increase of
the R3 group of WEEE that includes televisions sets, screens and
monitors. While the second is caused by the entry into force of LD 49/14
that receipts Directive 2012/19/EU and produced a new impetus on the
collection process. In the following section, both of these regulatory
effects are more deeply analyzed.
Transition Probability Matrix Results
In this section, the results deriving from the transition matrix analysis are presented.
Table
5 shows the transition probabilities for all the provinces for the
years 2008–2017. At the time of introduction of the WEEE's management
system (2008), as expected, the probability of a province being in LWC
state was very high (80%). At the end of the period (2017), such
probability dropped to 13.6%, while the probability of a province to
evolve into the MWC state was pretty high (20.5%), as for moving to HWC
(H1WC + H2WC + H3WC = 63.6%).
Table 5. Collection Centers: transition probabilities matrix of Italian provinces, 2008–2017.
2008–2017 |
LWC |
MWC |
H1WC |
H2WC |
H3WC |
Total (a) |
LWC |
14 (15.9%) * |
18 (20.5%) |
35 (39.8%) |
15 (17%) |
6 (6.8%) |
88 (80%) |
MWC |
1 (4.8%) ** |
1 (4.8%) |
9 (42.9%) |
8 (38.1%) |
2 (9.5%) |
21 (19.1%) |
HWC |
0 (0%) |
0 (0%) |
0 (0%) |
1 (100%) |
0 (0%) |
1 (0.9%) |
Total (b) |
15 (13.6%) |
19 (17.3%) |
44 (40%) |
24 (21.8%) |
8 (7.3%) |
110 (100%) |
Note:
integer indicates the number of provinces that passed from i state to j
state, while % indicates the transition probability, which is measured
by the ratio between the number of new provinces that passed from i
state to j state and the total number of provinces in the i state.
(a)=Probabilities of provinces being in a state at the beginning of the
period (2009); (b)=Probabilities of provinces being in a state at the
end of the period (2017). * Includes three Sardinia provinces
reorganized in 2017. In 2016, Carbonia-Iglesias, Medio Campidano and
Ogliastra were, respectively, in H1WC, MWC and H2WC. ** Olbia-Tempio
province (Sardinia) reorganized in 2017, in 2016 was in H3WC state.
The
MWC state was quite stable. The probability to remain in an MCW state
is low (4.8%), while it is very high for evolving in the HWC states (in
particular, 42.9% in H1WC, 38.1% in H2WC and 9.5% in H3WC). Thus, we can
say that provinces that have overcome the initial obstacles in
organizing the WEEE collection system have reached relevant performance.
Looking
at the initial HWC state, as expected, the probability of being in this
state is almost null (0.9%), while the probability to move in the
higher states (69.1%) is very high in the period considered. In
particular, only one province evolved from H1WC (4.2 kgpc) toH2WC (6.2
kgpc) state after ten years. As well as the probability to remain in the
HWC state being 1 (100%), thus this can be considered the sole
absorbing state for the period under analysis, even if limited by the
presence of only one province.
Carrying out a more detailed analysis
(Table 5), we have identified three groups of provinces on the basis of
the best and worst WEEE collection performance. Table 6 reports the
three groups according to the number of positions gained or lost in the
states of the probability transition matrix. The first two groups are
the groups of provinces that have collected more than 8kgpc and gained
more positions. In particular, the best performing provinces group
contains six provinces which have gained 5 positions starting
conditional on being in the LWC state. This group includes two Southern
provinces (Nuoro an Isernia, this last in 2017 was the best WEEE
collector with 14.57 kgpc) and four Northern provinces (among these was
Bologna, which collected 12.1 kgpc in 2017 with a growth of 35% compared
to 2016). These provinces are referred to as the "most virtuous" ones
and considered that their collection performance is more than three
times the 4 kgpc EU target.
Table 6. Group of best and worst performing provinces.
Group |
Description |
States Gained |
Province (Area) |
Best performing provinces (6) |
Collection rate > 8 kgpc and moved from LWC state to H3WC state. (More than virtuous provinces) |
5 |
Aosta (N) |
Gorizia (N) |
Bologna (N) |
Isernia (S) |
Como (N) |
Nuoro (S) |
Second-best performing provinces (2) |
Collection rate > 8 kgpc and moved from MWC state to H3WC state. (Virtuous provinces) |
4 |
Sassari (S) |
Trento (N) |
Worst performing provinces * (11) |
After ten years remained or recedes in LWC (Structurally blocked provinces) |
0 |
Agrigento (S) Barletta-A-T (S) Caltanissetta (S) Cosenza (S) Crotone (S) Enna (S) |
Foggia (S) Pescara (C) Siracusa (S) Taranto (S) Vibo V. (S) |
*:
The three Sardinia provinces Carbonia-Iglesias, Medio Campidano and
Ogliastra were in this group, but have been deleted because they were
reassigned in 2017.
The
second-best performing provinces group is that of the second highest
provinces, which improved their state of 4 positions conditional on
being in the MWC state. This group includes only two provinces, Sassari
(Southern Italy) and Trento (Northern Italy), which in 2017 collected
more than 8 kgpc. They are indicated as "virtuous".
The last group
includes the worst performing provinces of the class. In 2008, these
provinces were in the LWC and after ten years still remain in the same
last position. Eleven provinces belong to this group, which are almost
all located in Southern Italy. They are labeled as "structurally
blocked" because of their consolidated inability to progress in the WEEE
collection.
The data in Table 6 highlights the important feature of
the transition matrix method which provides the possibility of having
information on the dynamics of any specific province in order to
identify customized initiatives and policy actions to improve the
efficiency of the WEEE collection system.
The next step in the
analysis of the transition matrices was addressed to shed light on the
reasons of two different dynamics for the three areas in the periods
2008–2012 and 2013–2017. As mentioned in the descriptive results
(Section 5.2.), an interpretation of these trends was the impact of two
legislative events occurred in the period 2012–2014 on the performance
of the WEEE collection system. Table 7 shows the transition matrices for
the two sub-periods considered (2008–2012; 2013–2017) the first event
is the digital switchover occurred in 2012, which, by law, decreed the
technological obsolescence and the replacement of a large part of the
installed base of televisions sets. The second event is the entry into
force of the Legislative Decree 49/2014 which followed the introduction
of the EU directive 2012/19/EU, thus providing a potential impulse to
the e-waste collection.
Table 7. Transition matrix in Italy, 2008–2012 and 2013–2017.
|
LWC |
MWC |
H1WC |
H2WC |
H3WC |
Total (a) |
2008–2012 |
LWC |
13 (14.8%) |
30 (34.1%) |
35 (39.8%) |
9 (10.2%) |
1 (1.1%) |
88 (80%) |
MWC |
0 (0%) |
1 (4.8%) |
13 (61.9%) |
6 (28.6%) |
1 (4.8%) |
21 (19.1%) |
H1WC |
0 (0%) |
0 (0%) |
1 (100%) |
0 (0%) |
0 (0%) |
1 (0.9%) |
Total (b) |
13 (11.8%) |
31 (28.2%) |
49 (44.5%) |
15 (13.6%) |
2 (1.8%) |
110 (100%) |
2013–2017 |
LWC |
10 (62.5%) |
5 (31.3%) |
0 (0%) |
0 (0%) |
1 (6.3%) |
16 (14.5%) |
MWC |
3 (8.6%) |
14 (40%) |
17 (48.6%) |
1 (2.9%) |
0 (0%) |
35 (31.8%) |
H1WC |
1 (2.1%) |
0 (0%) |
27 (57.4%) |
16 (34%) |
3 (6.4%) |
47 (42.7%) |
H2WC |
0 (0%) |
0 (0%) |
0 (0%) |
7 (77.8%) |
2 (22.2%) |
9 (8.2%) |
H3WC |
1 (33.3%) |
0 (0%) |
0 (0%) |
0 (0%) |
2 (66.7%) |
3 (2.7%) |
Total (b) |
14 (12.7%) |
19 (17.3%) |
44 (40%) |
20 (18.2%) |
13 (11.8%) |
110 |
Note:
integer indicates the number of provinces that passed from i state to j
state, while % indicates the transition probability, which is measured
by the ratio between the number of new provinces that passed from i
state to j state and the total number of provinces in the i state. (a)
Provinces present in state at the beginning of the period, (b) Provinces
present in state at the end of the period.
The
transition probability matrix highlights that the first period is
featured by a higher mobility probability since the principal diagonal
probabilities are lower when compared with the second period (Table 7).
Moreover, when we consider the mean of the sum of probabilities which
are over the principal diagonal (which represents the improvement
trend), we can see that this mean is slightly higher for the first
period (20.1%) than for the second period (15.2%). Furthermore, the
probability of moving to the MWC a final time was moderately higher
(34.1% vs. 31.3%) for the first period. Similarly, the probability of
moving to the HWC a final time, conditional on being in the LWC at
initial time, was very relevant for the first period (51.1% vs. 6.3%).
Focusing on the MWC state, we can observe that the probability of moving
to the HWC a final time, was appreciably higher for the first period
(95.2% vs. 51.4%), while the probability of moving back to the LWC a
final time, conditional on being in the MWC at the initial time was
higher for the second period (+8.6%). Thus, we can conclude that the
legislative/technological event represented by the digital switchover
has provoked a higher positive impact on the 2008–2012 period when
compared with the effect of the legislative event represented by the
introduction of the LD 49/2014 on the period 2013–2017.