The increasing rate of urbanization along with its socio-environmental impact are major global challenges [1
]. The rising levels of urbanization are connected with the reduction of natural resources, the loss of biodiversity, soil degradation, and the pollution of the air, water, and land [3
]. Moreover, the deterioration of the environment is expected to increase in the future due to the growth of human population, especially in urban areas [4
]. The United Nations indicated that currently over 55% of the world’s population lives in urbanized areas, and this percentage is expected to increase to 68% by the year 2050 [5
]. This means that the world’s urban population might well rise from 4.2 billion people (2018) to 6.7 billion people in 2050 [5
]. Over half of the world’s countries already run ecological deficits, consuming more biocapacity than is available within their borders [6
]. The current rate of urban growth underscores the importance of urban areas as the focus of sustainability assessments [7
]. Therefore, there is a need to assess the state of balance and the boundaries to growth for future development of human settlements [8
]. The inclusion of the assessment of environmental carrying capacity (ECC) into the spatial management and planning of cities can be a useful tool for the development of sustainable human settlements [9
The ECC is a concept and tool used to assess the sustainable development level of a given area [10
]. The ECC verifies if the current spatial management is consistent or inconsistent with certain environmental restrictions and limitations, and it is poses limits to the ability of current and future populations to meet their needs. The ECC is most often assessed based on environmental indicators such as the ecological footprint (EF) and biocapacity (BC) [11
]. EF represents the human demand on nature (such as consumed resources, occupied space, and emitted pollutants) that compete for biologically productive space [15
]. Therefore, EF also indicates the biologically productive area needed to provide for all the competing demands on nature, from food production, fiber regeneration, infrastructure accommodation to sequestration of emissions [18
]. The BC represents the actual annual bioproductive ability of an area (an ecological benchmark) to provide the human needs [19
]. Thus, the BC assesses an actual annual ecosystem service budget available [19
]. This is a key ingredient for all of humanity’s goods and services. Despite that the ecological footprint accounting (EFA) can be applied to any scale. The national footprint accounts (NFA) are the most comprehensive attempt to assess countries’ footprint and biocapacity are based nearly exclusively on United Nations’ data [18
]. The NFA presents all steps of a national ecological footprint and BC assessment, from raw data to aggregated values of ecological footprint and BC. The NFA assessed the ecological footprint and BC for 242 countries and territories and the world as a whole [20
]. The results of the analyses are available for the period 1961–2014 [6
] and are provided by the Global Footprint Network. These accounts include the following land use types: croplands, grazing lands, fishing grounds, forest lands, carbon uptake land, and built-up lands [20
]. Cropland consists of the area required to grow all crop products, including livestock feeds, fish meals, oil crops, and rubber. The grazing land represents the crop feeds to support livestock. The grazing land comprises all grasslands used to provide feed for animals, wild grasslands, and prairies. The fishing grounds are represented the annual primary production required to sustain a harvested aquatic species. The forest land reflects the annual harvests of fuelwood and timber needed to supply forest products. The uptake land shows the contamination of a waste product, namely carbon dioxide. The CO2
is released into the atmosphere from a variety of sources, including human activities such as burning fossil fuels and certain land use practices; as well as natural events such as forest fires, volcanoes, and respiration by animals and microbes. The built-up area represents the land covered by human infrastructure: housing, industrial structures, transportation, and reservoirs for hydroelectric power generation [21
Note that EFA only accounts for the human requirement for bioproductive areas, and does not include productive areas required to maintain other species. Both EF and BC are expressed in the same units, global hectares (gha), which means that both indicators can be compared. This unit, global hectares, is the result of the conversion of the total physical area of a given land use type of a given country into its equivalent global productivity (gha). The conversion is based on the ratio of its productivity to the global average biological productivity [22
]. A minimum and conservative environmental condition, on average, is to reach a quotient of EF and BC smaller than one; the goal is minimum and conservative because it does not include the reservation of productive ecosystems for the maintenance of biodiversity, which has been estimated to be between 11% and 75% [16
]. In case the EF exceeds the BC (or the available portion thereof), that population is running an ecological deficit. In a closed system such as the Earth, an ecological deficit at the global level is an indication of global ecological overshoot. It manifests as ecosystem degradation, loss of natural capital, or the accumulation of waste. However, at the city or country level, the excess biocapacity demand can be met through the import of external goods. When BC is greater than EF, that entity corresponding to an ecological reserve [16
Currently, the assessment of BC and EF is well-developed on the global [22
] as well as on the national level [15
]. However standardized calculations [26
] and comprehensive assessment on regional [12
] and city level are limited [18
]. In Central Eastern Europe (Figure 1
), there is an apparent lack of EF assessments on the city level. This phenomenon could be attributed to a scarcity of data sources and limited comparability, i.e., a use of different data sources and assumptions within the calculations [18
]. However, in other regions, EF assessments have been applied for individual cities across various countries [19
Understanding and monitoring the resource metabolism of cities is critical in order to inform municipal actions and decision-making as part of the larger goal of global sustainability [36
]. The analysis of current state of the environment could allowed to understand the connection between the local consumption and exploitation of resources and its global environmental impact [34
]. Such assessment allows for increase of resources exploitation responsibility, as well as for evaluation of resource-related risk [37
]. Moreover, it increases resource efficiency and decreases the risk associated with natural resources [37
]—including food security [38
]. Food is a basic need of households, thus the assurance of the food security is widely recognized as the greatest challenge to sustain humanity in the 21st century [41
]. World population is expected to reach 9 billion by 2050 [4
] and population living in cities is also estimated to increase, intensifying the demand for resources [4
]. The increasing demand for natural resources, which provide fundamental ecosystem services to city dwellers, such as food production, is directly related to urban growth [36
]. On one hand, the ongoing urbanization process is leading to significant land use changes in the territory due to the expansion of artificial areas, causing loss of habitats, cropland, and grazing areas. On the other hand, the increasing number of inhabitants would require more cropland areas to produce food, which could be already lost [42
]. The Food and Agriculture Organization of the United Nations (FAO) expects an increase of food production by at least 60% from 2006 to 2050 [40
] and an increase in the demand for energy due to the intensification of agriculture, as well as an increase of pollution emitted to the environment [18
]. Therefore, this study deals with the application of EF at the city level as a measure of ECC. The paper focuses on ecological footprint of food (EFF
) and comparing hybrid EFF
assessment (combining a bottom-up carbon footprint of food (CFF
) with remaining top-down EFF
’s components) with full top-down assessment for food EF. Thus, the research would verify if the use of a hybrid method allows for a comparison with a top-down approach. Especially, that other researchers indicated the need for the development of international urban ecological footprint standards towards a hybridization of top-down and bottom-up approaches [18
The study compares the obtained values of EFF
using both methods, as well as compares EFF
’s with biocapacity benchmark as an indicator of sustainability. The difference of EFF
’s and BC would indicate if ECC of analyzed city is exceeded or not. The rationale for this study is the assumption that the implementation of the ECC into spatial management is relevant to increase the efficient of long-term planning [44
], the use of natural resources [45
], as well as for the assurance of the food security [41
] in the context of sustainable development.
4. Discussion and Conclusions
The results of this study indicated, that the EFF
exceeded the current biological potential of the city of Wrocław, which could be categorized as ecological debtor. However, there should be underlined that cities are centers of population, and by extension, centers of resource aggregation, and consumption. Therefore, it generally should be expected that all major cities are ecological debtors. The latest research of EF and BC at national level showed, that Poland’s BC per capita was 2.08 gha [62
]. This means, that EFF
of Wrocław is 46–47% of Poland’s biocapacity.
The Wrocław’s EFF
exceeded its BC by about 10 times, which means also the exceeding of the environmental carrying capacity of Wrocław. Considering that Poland’s ecological footprint of food is about a quarter of the total EF (1.0 gha per capita per year vs. 4.4 gha per capita per year, respectively) [62
], the total EF for Wrocław, which includes transportation, housing, goods, and services could be higher than the EFF
calculated here. The EFF
per capita was assessed as 0.963–0.974 gha per capita per year. The Wrocław’s EFF
may be compared with values calculated for Mediterranean countries, where an average EF was 0.9 gha per capita per year [63
]. The highest value of EF had Portugal with an EF reaching 1.5 gha per capita per year. The lowest value had Slovenia with 0.63 gha per capita per year [63
]. The obtained differences could be connected with number of components taking into consideration in each research. Wrocław’s EF included only one of the total EF categories—food footprint. The research conducted by Galli et al. [63
] take into consideration also others sources and goods consumed by households, such as clothing and footwear; housing, water, electricity, gas and other fuels; furnishings, household equipment; transportation, etc. Therefore, future research should implement further categories. Moreover, the obtained differences would be connected to the nutrition habits of the Polish people. Meat and its products dominate in the everyday diet [64
One of the major challenges of sub-national ecological footprint assessments is data availability. This limitation applies to both top-down and bottom-up calculations, and to overcome this limitation requires significant effort, either in developing and implementing surveys or time-intensive LCA for both CO2 and additional ecological footprint components. Without sufficient data, bottom-up calculations are severely limited and inaccurate simply because of lack of completeness. LCA approaches are generally advantageous for calculating the carbon footprint because they include full upstream supply chain emissions, and are very location specific, however they tend to be very time intensive and more difficult to apply for tracking non-CO2 footprint components. Thus, applying a hybrid top-down approach allows for missing categories to be supplemented with scaled estimates. Here we show that the difference between these approaches is relatively minor.
Although the research was based on universal data, as representative European food basket products, and indices for CO2eq emission of food consumption in Europe, some data were still unavailable or classified in another manner in the available reports. Therefore, bottom-up CFF assessment, based on the LCA method, also has some limitations:
The report, on average monthly consumption of selected foodstuffs per capita in households by class of locality or regions/voivodeships, did not have information on consumed products as beef, pork, and beer. Thus, these data had to be assumed from report on the national annual amount of consumption of a given product.
There was no information about meat-based meals on the level of the city’s and region’s accuracy, as well as national level.
The report did not include some food products—i.e., olive oil and sunflower oil—but contained the integrated information about the consumption of vegetables fats. Therefore, the CO2eq factor for this group was assumed as an average value from these two products. Thus, the value for this product group could be undervalued.
The European food basket includes two products from the ‘fruits’ group, namely oranges and apples. However, the information about the consumption of oranges was unavailable in Polish reports. Despite this, there was available information on the consumption of citrus fruit and bananas. Therefore, we decided to assume the value of oranges’ CO2eq to this product type. The information of the consumption of apples was available, thus no additional assumption for this product type was required.
The research showed that the highest impact on the CFF
had the product groups ‘meat and seafood’, ‘beverages’, and ‘dairy products’. Usually, the highest impact of food consumption have the meat and dairy products [58
]. The obtained results fit partially into the literature-based model. Therefore, the use of representative food products could be considered as a limitation in this context.
The analysis used food data from different levels, which was connected with lack of some data at the city level. Despite this, the hybridization of top-down and bottom-up approaches allowed for a comparison of the obtained results from a top-down approach.
It should be noted that the baseline for calculation was the year 2016. However, we used data from 2016 (food consumption, land use), 2014 (YF, EQF, carbon dioxide sequestration index) and 2013 (CO2eq for each food product). Therefore, the analysis requires recalculation based on data for the year 2016 when these data become available.
The analysis based on European universal data of CO2eq
, which presents the amount of CO2eq
emitted during whole life cycle of given product. Note that there may be differences in the cultivation of the same products in the same area, but in different ways—organic or intensive farming [65
], which could have an impact on the assessed CFF
. Moreover, our analysis did not include food waste and—connected with this phenomenon—the recycling technologies. The use of various types of food waste recycling allows for the minimization of contamination and increasing of recycling rates [66
]. Food waste is one of the major problems in modern society [67
]. Therefore, such assumptions should be verified in future analyses and studies.
The presented bottom-up, as well as the top-down approach showed some limitations. First one characterizes the incomparability of results with top-down approach. This means that the bottom-up approach better described local condition, without comparison to sub-national results. On the other hand, the top-down approach not adequately reflect local situations [55
]. Therefore, the verification of hybridization of top-down and bottom-up approaches [18
] and its comparability to top-down approach is desirable.
The proposed bottom-up CFF assessment could increases the comparability of results between European cities. Especially that finally the difference of top-down EFF and hybrid EFF was 1.2%. Thus, the research verified that the use of hybrid method allows for comparability with top-down approach. This, in turn, could also increase the comparability of the ECC of cities. Thus, future research directions should be connected with development of ecological footprint at city level defined by more categories than food. The EFF might be used for the assessment of ECC within other administrative units, such as municipalities, regions, or even at the national level. The implementation of EFF into ECC would allow for understanding the city residents’ lifestyle and consumption, which should be a base for creating future long-term spatial policy, other action plans connected with adaptation to climate change and reduction of greenhouse gas emissions or food security policy.
The analysis of food consumption allows for an evaluation of resource bases to ensure food security, as well as for estimating the food consumption pressure [48
]. Moreover, the proposed assessment might be used for other research aspects, such as for ecosystem services assessment or foodshed analysis. The approach of EFF
as a part of ECC presented in this research allowed for the assessment of the human impact based on environmental resources consumption and the related emission at a local or city level. The obtained results pointed, that even one component of EF assessment could verify if current development, and connected with it resources exploitation, might surpass the ECC of given city.