Trends and Pressures
The social, financial and environmental setting of every city is unique. This context may result in different priorities per city and their ability to attain sustainable IWRM. Indicators aimed to foster sustainable IWRM, should measure solely IWRM performances. A typical example is the limited natural availability of fresh water which may cause water stress for cities in (semi)arid regions. In this case, descriptive indicators measuring water availability would score low while the city may be a frontrunner in water efficiency practices precisely because they have to cope with limited water resources. Solely measuring urban performance to reduce water consumption allows for a fair comparison between cities and, more importantly, fosters sustainable practices in all cities participating in a city-to-city learning alliance. The main task of the TPF here is to identify priorities. In this case priorities may be the application of water saving measures by consumers, as well as infrastructure leakage reduction by water utilities. Hence, the TPF provides a wider context and allows for a quick overview of the most important limitations and windows of opportunity for IWRM.
Urban environmental pressures need to be reduced while social and financial living standards have to be sufficient to enable a good quality of life (Mori and Yamashita 2015). Hence, social, environmental and financial aspects are considered as equally important and are therefore covered by an equal number of indicators. All 12 indicators (Table 2) are scaled from 0 to 4 points, and the following classes have been used: 0–0.5 points (no concern), 0.5–1.5 (little concern), 1.5–2.5 (medium concern), 2.5–3.5 (concern), and 3.5–4 (great concern). Figure 1 shows the result of the aggregated score, i.e., the TPI for the 45 cities. The overall TPI provides a basic overview of the social, environmental and financial pressures. All cities in north western Europe have low TPIs. Mediterranean and eastern European cities already experience moderate pressures, while big cities such as Belém, Ho Chi Minh City, Istanbul, Dar es Salaam and Kilamba Kiaxi have high TPIs.
The Improved City Blueprint Framework
The CBF has been modified to obtain an approximately proportional contribution of all indicators and categories to the overall score, i.e., the improved BCI (BCI*). This was done by analyzing correlations and variances, as well as by balancing and regrouping the different indicators. Six indicators have been removed because of data inaccuracy, overlap / redundancy, or lack of focus on IWRM. Seven indicators have been added, i.e., secondary and tertiary wastewater treatment (WWT), operation cost recovery, green space and three indicators belonging to the category ‘solid waste treatment’. Furthermore, the geometric aggregation method has been selected for the calculation of the BCI* because it emphasizes the integrative nature of IWRM by penalizing unbalanced indicator scores (Koop and Van Leeuwen 2015a).
The BCI (arithmetic average of the old 24 indicators) and the BCI* have been calculated for the same 45 cities. The BCI* shows more distinctiveness compared to BCI, since the variance is 2.5 times larger. The BCI ranges from 3.6 for the city of Belém (Brazil) to 8.5 for the city of Helsingborg (Sweden) which is a difference of 5.1 points. The BCI* ranges from 1.1 for the city of Belém (Brazil) to 8.3 for the city of Amsterdam (Netherlands) which is a difference of 7.2 points. The differences in the BCI and the BCI* are shown in Fig. 2.
Cities that already received a low BCI got even lower BCI* scores. On the contrary, cities that already had high BCIs, received slightly lower BCIs*. The city of Amsterdam is an exception (Fig. 2). The lower scoring cities showed the largest decrease in the overall BCI* compared to their old BCI, which is the result of the geometric aggregated mean as this method penalizes unbalanced scores. The ranking of the cities has not changed considerably and the BCI and BCI* correlate strongly with a Pearson correlation coefficient (r) of 0.92 (Fig. 3). The BCI* is negatively correlated with the overall TPI (r = −0.83; Fig. 3). Cities that experience high social, environmental and/or financial pressures, generally perform low on IWRM.
The BCI* and TPI have been compared with other indices and parameters that describe the state of cities and countries. It should be emphasized that correlations are not cause-effect relations. The BCI* correlated remarkably well with the Notre Dame Global Adaptation Index (ND-GAIN) climate readiness index (r = 0.86). This index measures the country’s ability to absorb financial resources and mobilize them efficiently to adapt to climate change by taking into account economic, governance and social factors that contribute with 50, 25 and 25 %, respectively (ND-GAIN 2013). The ND-GAIN climate readiness index correlated highly with the BCI* (Fig. 4) and even better, but negatively, with the TPI (r = −0.94; Table 4). It means that cities that perform well on IWRM are cities that are also climate-ready.
Other correlations between the BCI* and TPI show the same pattern and are summarized in Table 4. Interestingly, the BCI* is also strongly correlated with the Environmental Awareness Index (EAI; Harju-Autti and Kokkinen 2014). Furthermore, correlations with public participation, measured by the involvement in voluntary work are high (EFILWC 2012). The BCI* and TPI correlate very well with all World Bank governance indicators (World Bank 2015), in particular with government effectiveness.
Performance of Cities: Main Results
It is impossible to address the detailed results of each and every City Blueprint and TPF of the 45 cities, but examples for cities have been provided by Koop and Van Leeuwen (2015a, 2015b ). In this paper we summarize the main findings.
The lack of basic water services and the absence of environmental protection measures in cities in developing and transition countries, such as Dar es Salaam, Ho Chi Minh City, Belém and Istanbul is staggering. These cities have a secondary WWT coverage of less than 30 %. Overall, still 11 of the 45 cities have secondary WWT coverage of less than 50 %. These low coverages pose serious threats to ecosystem and human health. For 19 of the 45 cities and regions, tertiary WWT is below 50 % coverage. This includes all eastern European cities, whereas most cities in western Europe have high coverages.
Nutrient recovery from wastewater is important to decrease surface water pollution as well as to reduce our dependency on non-renewable resources. This holds especially for phosphorous and potassium as these resources will become increasingly expensive as they are difficult to obtain (Cordell and White 2011; EC 2014). About half of the cities do not apply any form of nutrient recovery. The reuse of nutrients can either be done directly by applying sewage sludge on agricultural land or indirectly by producing struvite (MgNH4PO4.6H2O) from wastewater. Struvite can be used as a fertilizer, e.g. in parks or sport fields as is done in Amsterdam (Van Leeuwen and Sjerps 2015a). The production of struvite is a good alternative if direct application of sewage sludge is legally restricted or banned as a result of health or economic concerns. Currently, many cities do not apply nutrient recovery because they are either not aware or a market to apply struvite is lacking.
Eleven cities do not apply any form of energy recovery techniques at the wastewater treatment plants while this can be considered as a CO2-neutral way of energy generation. Moreover, 30 cities used less than 50 % of their potential to apply energy recovery from their solid waste. German cities even burn 21 % of their total solid waste without energy recovery (OECD 2013). On average 47 % of the solid waste ends up in landfills where it produces large amounts of greenhouse gasses and may lead to water pollution, especially when the site management is insufficient ( Rosik-Dulewska et al. 2007; Lazarevic et al. 2010).
The average infrastructure leakage rate for 45 cities and regions is considerable, i.e., 21 %. Seven cities had leakage rates that exceeded 40 %. Stormwater separation is applied in 49 % of the water infrastructures in the cities in this study. It is remarkable that Copenhagen and almost all Dutch cities have high BCIs* but low separation rates (less than 12 %). As a consequence, combined sewage overflows, urban drainage flooding, both exacerbated by climate change, may seriously affect water quality and biodiversity. This may lead to damages from extreme weather events that are projected to increase significantly (Jongman et al. 2014).
Green space coverages (%) differed largely per city with 40 % or more for most Scandinavian cities and on the other hand less than 15 % for Athens, Bucharest and all developing cities. A low share of green area increases the vulnerability to urban drainage floods and heat waves (EEA 2012). Increasing green space in cities is important and may result in multiple co-benefits for health, the economy, society and the environment. Hence, this nature-based measure often represents a more efficient and cost-effective solution than more traditional approaches (EC 2015b). Furthermore, the future damage as a result of inaction is often more costly than the necessary investments (EEA 2012; Klein Tank and Lenderink 2009).
The focus of this paper has been on the performance of IWRM in European cities. Nevertheless, we have tried to include also other geographical regions. The selection of cities is therefore not random at all, but regionally biased towards western Europe. With these limitations in mind we have clustered cities into distinct categories of sustainability regarding their IWRM. The categorization is based on the BCI* scores and the CBF indicators for 45 cities in 27 different countries. The suggested categorization is supported by the results of a hierarchical clustering analysis (Fig. 5). Three broad categories can be identified(Fig. 5 with squared Euclidean distance > 12). One category includes most Scandinavian and Dutch cities which typically have high BCI* values varying from 6 to 8. Next, a category including a variety of cities with average BCI* values between 4 and 6. Finally, a third category is identified that includes cities in developing and transition countries and many cities from eastern Europe. The BCI* values range from 0 to 4. However, the developing cities (Dar es Salaam, Kilamba Kiaxi, Belém and Ho Chi Minh city) appear to be substantially different from the other cities in this category. These cities also have the lowest BCI* values with values in the range of 0 to 2. Moreover, these cities do not meet their basic water services such as access to drinking water and sanitation, whereas cities in the BCI* range of 2 to 4 have almost full coverage of basic water services (Fig. 6). As basic water services are key for human life, cities which lack basic services are categorized separately. Based on Fig. 5 and the indicator scores of 45 cities, and in particular some key indicators as shown in Fig. 6, we propose a simple categorization of the different levels of sustainability for IWRM in cities (Table 5; Fig. 7).