Traditional ecological footprint consumption accounts
To truly reflect the ecological footprint and ecological carrying capacity of Dongying city, according to the lifestyle and consumption of Dongying city and with reference to Shandong Province Statistical Yearbook and Dongying City Statistical Yearbook, the biologically productive land is divided into arable land, forestland, grassland, water, construction land and fossil energy land, and the main consumption items of each category are shown in Fig. 3.
Traditional ecological footprint consumption accounts in Dongying city. This paper uses the carbon footprint to improve the fossil energy footprint of the traditional ecological footprint.
NPP-based correction of ecological footprint parameters
The 30 m land use of the study area was resampled to 500 m, consistent with the resolution of MOD17A3H after pre-processing with MRT and other tools. Correction of ecological footprint parameter factors in Dongying City for 2015, 2018 and 2020 based on the annual average NPP of vegetation (Table 1). This method is faster and more accurate than other methods, and the implementation of NPP calculations from the vegetation light energy use efficiency (LUE) framework to correct ecological footprint parameters is more applicable and accurate than other methods.
Yield factor
The formula for calculating the yield factor for arable land in the Yellow River Delta refers to NFA 2016:
$$left{ {begin{array}{*{20}c} {Y_{j1} = frac{{Sigma A_{W} }}{{Sigma A_{N} }}} {A_{N} = frac{{P_{N} }}{{Y_{N} }}} {A_{W} = frac{{P_{N} }}{{Y_{W} }}} end{array} } right.$$
(1)
In Eq. (1), ({Y}_{j1}) is the yield factor of the arable land in the study area, ({A}_{N}) is the harvested area ( culture area ) of agricultural products of category (N) in the study area, ({A}_{W}) is the area required to produce an equivalent amount of this type of agricultural product based on the world average yield, ({P}_{N}) is the production of agricultural products of category (N) under the region, ({Y}_{N}) is the average yield of agricultural products of category (N) under the region, and ({Y}_{W}) is the world average production of a category of agricultural products.
The NPP products from MODIS supported by remote sensing were used as the base data to correct the yield factors of woodlands and grasslands in the study area under the ecological footprint model.
$$Y_{{{text{j}}2}} = overline{{NPP_{local} }} /overline{{NPP_{global} }}$$
(2)
In Eq. (2), ({Y}_{mathrm{j}2}) is the yield factor for woodland and grassland in the study area, ({NPP}_{local}) is the average annual net primary productivity of woodland and grassland in the study area in the corresponding year, and ({NPP}_{global}) is the global average NPP of woodland and grassland in the corresponding year, referring to Amthor et al.24.
In addition, most of the land for construction comes from cropland, so the yield factor for construction land is the same as that for cropland25. The yield factors for the watershed were derived from the Wackernagel and Rees26 study.
Balancing factor
The NPP model for provincial hectares was applied to the municipal scale. Among them, the NPP of four biologically productive lands, namely cropland, woodland, grassland and water, was weighted and summed to obtain the annual average NPP within the city area.
$$overline{NPP} = frac{{mathop sum nolimits_{j} left( {A_{j} times NPP_{j} } right)}}{{mathop sum nolimits_{j} A_{j} }}$$
(3)
In Eq. (3), (overline{NPP }) is the average net primary productivity of arable land, forestland, grassland and water in Dongying, ({A}_{j}) is the area of land in category (j), and ({NPP}_{j}) is the average annual NPP of productive land in category (j).
Balancing factors for arable land, woodland, grassland and water in the Yellow River Delta.
$$R_{j} = frac{{NPP_{j} }}{{overline{NPP} }}$$
(4)
In Eq. (4), ({R}_{j}) is a balancing factor.
The sites for construction are located in areas suitable for agricultural cultivation or directly occupy arable land, so the potential ecological productivity of urban construction land is the same as that of arable land, and therefore the equilibrium factor for construction land is equal to that of arable land27.
Ecological footprint principles and improvements
Ecological footprint model
Ecological footprint model includes ecological footprint, ecological carrying capacity and ecological deficit. As the study area is within the city limits and the statistics have their own characteristics, adjustments have been made to the methodology for calculating the national ecological footprint accounts28. Based on the biological consumption account, the ecological footprint can be calculated for any land use type.
$$EF = frac{P}{{Y_{N} }} times R_{j} times Y_{j}$$
(5)
In Eq. (5), (P) is the number of biologically productive land harvesting consumption items in a category, and ({Y}_{N}) is the average production of consumption Item (N) in the region. The ecological footprint of the construction land is measured based on the area of human infrastructure land and is equal to its ecological carrying capacity.
Ecological carrying capacity is the determination of the maximum carrying capacity of an ecosystem for human activity, expressed as the sum of the biologically productive land area available in an area.
$$EC = N times ec = N times sum left( {a_{j} times R_{j} times Y_{j} } right)$$
(6)
In Eq. (6), (EC) is the ecological carrying capacity per capita, and ({a}_{j}) is the per capita area of biologically productive land of category j in the region. According to the recommendations of the World Commission on Environment and Development, 12% of the ecological carrying capacity should also be deducted for biodiversity conservation. The population figures for the study area were obtained from the statistical yearbook and the seventh national census data. According to the recommendations of the World Commission on Environment and Development, 12% of the ecological carrying capacity should also be deducted for biodiversity conservation.
An ecological deficit is the interpolation of the ecological footprint and ecological carrying capacity.
$$ED = EF – EC$$
(7)
When (ED>0) indicates an ecological deficit, the ecological environment has exceeded the carrying capacity. Conversely, when (ED<0), the ecology of the study area is in surplus.
Land use carbon emissions
Based on the research of domestic and foreign scholars, this paper divides the carbon emission calculation of land use into a direct calculation method and an indirect calculation method, in which arable land, grassland, forestland, water area and garden land are the direct sources of carbon emissions, so the direct calculation method of carbon emissions is used; construction land is the indirect source of carbon emissions, so the indirect calculation is based on the carbon emissions generated after the fossil energy consumed by construction land.
(1) Direct calculation of carbon emissions.
Carbon emissions from arable land, forestland, grassland, water, garden land and unused land are non-building land, and their carbon emissions mainly come from the energy consumption of agricultural machinery, fertilizer application, biological respiration and decomposition of soil organic matter29, so they are calculated using the direct carbon emission calculation method.
$$C = mathop sum limits_{i = 1}^{n} T_{i} = mathop sum limits_{i = 1}^{n} e_{i} times delta_{i}$$
(8)
In Eq. (8), (C) is the total carbon emissions of a site category, ({T}_{i}) is the carbon emissions from land type (i), ({e}_{i}) denotes the area of land in category (i), ({delta }_{i}) is the carbon emission factor (carbon sequestration factor) for land type (i), Carbon emission is positive and carbon sink is negative. As shown in Table 2.
(2) Indirect calculation of carbon emissions.
Since the calculation of carbon emissions from construction land is not suitable for direct estimation, the method of indirect estimation by constructing a carbon emission model for energy consumption is adopted35. The main types of energy consumed in the Yellow River Delta are coal, coke, crude oil, fuel oil, gasoline, and paraffin.
$$E = sum T_{i} times alpha_{i} times beta_{i}$$
(9)
In Eq. (9), (E) stands for total carbon emissions from fossil energy combustion, ({T}_{i}) denotes the total consumption of fossil energy in category (i), ({alpha }_{i}) is the coefficient of conversion of category (i) fuel consumption into standard coal, and ({beta }_{i}) is the carbon emission conversion factor when type (i) energy is consumed. As shown in Table 3.
Improvement ecological footprint based on carbon footprint
The ecological footprint of energy land reflects the degree of pressure on the surrounding ecological environment caused by the consumption of fossil fuels by human activities and economic development. The traditional method of measuring the ecological footprint of energy land mainly considers the CO2 emitted after the combustion of fossil energy. This paper takes into account the difference in carbon emissions during the land use process, based on the traditional ecological footprint consumption account, and replaces the traditional ecological footprint of energy land with a carbon footprint, which can better reflect the change pattern of carbon emissions in the total ecological footprint during human activities and is closely integrated with the IPCC land use carbon emissions study. It is also possible to take into account the impact of carbon emission factors on the carbon sequestered land in the ecological footprint.
$$EF_{C} = frac{{left( {E_{g} + E_{j} + E_{w} } right)}}{NP}$$
(10)
In Eq. (10), ({EF}_{C}) is the carbon footprint, ({E}_{g}), ({E}_{j}) and ({E}_{w}) denote the total annual CO2 emissions from cropland, construction land and unused land respectively, and (NP) is the average carbon sequestration capacity of grasslands, woodlands, gardens and watersheds, t/hm2.
Gridded ecological footprint model
While traditional ecological footprint estimation often takes administrative districts as the basic unit, the grid ecological footprint can show the spatial distribution of the ecological footprint within the study area at a large scale, free from the limitations of administrative units, and this method is more intuitive and accurate.
$$Ef_{j} = frac{{EF_{i} }}{{P_{i} }} times p_{j}$$
(11)
In Eq. (11), ({Ef}_{j}) indicates the ecological footprint of the grid, ({EF}_{i}) and ({P}_{i}) denote the total ecological footprint and total population of the ith city respectively, and ({p}_{j}) is the population density of grid (j).
$$Ec_{j} = sum R_{j} times Y_{j} times a_{ij}$$
(12)
$$Ed_{j} = Ef_{j} – Ec_{j}$$
(13)
In Eqs. (12) and (13), ({Ec}_{j}) denotes the ecological carrying capacity of the grid, ({a}_{ji}) denotes the area of productive land of category (i) in grid (j), and ({Ed}_{j}) denotes the grid ecological deficit.
Decoupling carbon emissions from economic growth
To develop a sound green economic system and empower China to ‘double carbon’, it is necessary to strengthen the management of carbon in the process of economic development and improve energy-based economic growth. Therefore, this paper introduces the decoupling relationship between carbon emissions and economic growth, and uses the three indicators of economic carbon emission factors (R), (Delta GDP) and (Delta {CO}_{2}) as the basis for judging the degree of decoupling between carbon emissions and (GDP)(Fig. 4), which is of great practical significance for formulating reasonable low-carbon emission reduction plans, reducing ecological pressure and promoting high-quality development.
Types of decoupling of economic development and carbon emissions.
Tapio constructed the decoupling elasticity coefficient by calculating the ratio of the change in environmental pressure to the change in total economic volume. Based on this, this paper constructs a decoupling elasticity coefficient between carbon emissions and economic growth as a way to portray the synergistic relationship between carbon and the economy in the process of vigorous economic development in the Yellow River Delta (Table 4).
$$R = frac{{left( {C^{i} – C^{i – 1} } right)/C^{i – 1} }}{{left( {GDP^{i} – GDP^{i – 1} } right)/GDP^{i – 1} }}$$
(14)
In Eq. (14), ({C}^{i}) denotes the carbon emissions in year (i), ({C}^{i-1}) denotes the carbon emissions in year (i-1),and ({GDP}^{i}) and ({GDP}^{i-1}) denote the total economic output in years (i) and (i-1), respectively.
Source: Ecology - nature.com
