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Measurement and assessment of carrying capacity of the environment in Ningbo, China
Journal of Environmental Management 92 (2011) 2047e2053
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Measurement and assessment of carrying capacity of the environment in Ningbo, China R.Z. Liu a, *, Alistair G.L. Borthwick b a
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China b Department of Engineering Science, University of Oxford, Parks Rd., Oxford OX1 3PJ, UK
a r t i c l e i n f o
a b s t r a c t
Article history: Received 5 October 2010 Received in revised form 19 February 2011 Accepted 24 March 2011 Available online 19 April 2011
Carrying Capacity of the Environment (CCE) provides a useful measure of the sustainable development of a region. Approaches that use integrated assessment instead of measurement can lead to misinterpretation of sustainable development because of confusion between Environmental Stress (ES) indexes and CCE indexes, and the selection of over-simple linear plus models. The present paper proposes a comprehensive measurement system for CCE which comprises models of natural resources capacity, environmental assimilative capacity, ecosystem services capacity, and society supporting capacity. The corresponding measurable indexes are designed to assess CCE using a carrying capacity surplus ratio model and a vector of surplus ratio of carrying capacity model. The former aims at direct comparison of ES and CCE based on the values of basic indexes, and the latter uses a Euclidean vector to assess CCE states. The measurement and assessment approaches are applicable to Strategic Environmental Assessment (SEA) and environmental planning and management. A case study is presented for Ningbo, China, whereby all the basic indexes of ECC are measured and the CCE states assessed for 2005 and 2010. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Carrying capacity Measurement Strategy environmental assessment Environmental planning Ningbo
1. Introduction The term carrying capacity was coined in the late 1890s by range managers concerned with the use of land for grazing livestock (see e.g. Bartels et al., 1993). In the 1970s, Godschalk and Parker (1975) explored the use of three types of environmental, institutional, and perceptual carrying capacity in natural and man-made systems. Subsequently, environmental carrying capacity became a valuable tool for environmental planning and management (Baldwin, 1985; Zeng et al., 1991; Ye, 1992). Carrying capacity has also been called ecological capacity (Rees, 1992; Wackernagel and Rees, 1996), ecological resilience (Arrow et al., 1995), and ecological carrying capacity (Wang et al., 2000; Prato, 2009), when applied to local, regional, and urban systems (Yu and Mao, 2002; Oh et al., 2005). Carrying capacity has also evolved into social carrying capacity (Daily and Ehrlich, 1996), cultural carrying capacity (Hardin, 1986; Seidl and Tisdell, 1999), and tourism carrying capacity (Saveriades, 2000; Prato, 2009). However, carrying capacity remains a highly elusive concept and its implementation is
* Corresponding author. Tel.: þ86 010 59893106; fax: þ86 010 59893086. E-mail address: [email protected] (R.Z. Liu). 0301-4797/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2011.03.033
hindered by practical problems involved in its measurement (Papageorgiou and Brotherton, 1999). The hypothetical counting of natural resources, environmental quality standards for air and water, and socio-economic statistics cannot provide an accurate, comprehensive measure of carrying capacity (see e.g. Tang and Ye, 1998; Yu and Mao, 2002). In practice, carrying capacity is often estimated by comparing stress on the environment (e.g. demand of natural resources or ecological footprint) against environmental thresholds (e.g. available natural resources or ecological capacity) (see e.g. Wackernagel and Rees, 1996; Tang and Ye, 1998; Yu and Mao, 2002; Clarke, 2002; Oh et al., 2005). But most of these conventional assessments do not provide correct results because they misrepresent the stress, state, and threshold of the environment. Bearing in mind this experience, the present paper focuses on the Carrying Capacity of the Environment (CCE), which provides a powerful tool for Strategic Environmental Assessment (SEA) (Thompson et al., 1995; Ng and Obbard, 2004) and environmental planning and management (Godschalk and Parker, 1975; Baldwin, 1985). A new definition of CCE is made, noting future use and remediation of the environment. Next, a specific, comprehensive measurement of CCE for a certain region is proposed, and an integrated assessment of CCE (namely the vector-surplus ratio of carrying capacity model based on stress and carrying capacity) is developed.
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2. Materials and methods 2.1. Study area As a major deep-water port for foreign trade, Ningbo has become an important industrial and economic center in Zhejiang Province, China. Ningbo is located in the middle of the eastern seaboard of mainland China, to the South of the Yangtze River Delta (see Supplementary Fig. 1). Zhejiang Province has a subtropical monsoon climate, characterized by mild temperature, moderate humidity and distinct seasons. Hills and mountains occupy more than 50% of the land area. Three major rivers flow through the plains of Ningbo: the Yaojiang River, the Fenghuajiang River, and the Yongjiang River. Ningbo occupies a total land area of 9695 km2, and comprises six districts (Haishu, Jiangdong, Jiangbei, Zhenhai, Beilun and Yinzhou), three county-level cities of Yuyao, Cixi and Fenghua, and two counties of Xiangshan and Ninghai. In 2005, the total population of Ningbo was 5.57 million, of whom 1.83 million resided in urban areas. Its economic development is based on advanced manufacturing, petrochemical, energy, iron and steel, papermaking, shipbuilding, and service industries. In 2005, the gross domestic product of Ningbo was 245 billion RMB, and its industrial surplus was 135 billion RMB. However, this tremendous economic achievement has placed a heavy burden on the environment of Ningbo. In 2005, the concentration of sulfur dioxide in the air reached 0.047 mg/m3, close to the National Secondary Standard of 0.060 mg/ m3. The Air Pollution Index (API) indicated that air pollution levels harmful to human health occurred on 35 days in 2005. Water was severely polluted, with high concentrations of COD in urban waters and stagnant rivers. The average water resource available per annum per person in Ningbo was a mere 1285 m3, far below the average of 2100 m3 for Zhejiang Province. Land available for building development became scarce, exacerbated by the amount of land already taken for agrarian and industrial development. The local ecosystem was damaged as forests and beach wetlands were replaced by land development projects.
environmental, ecological and social implications. The resource implication of CCE relates to the threshold of available natural resources for human demand in the environment, which is the original, primary meaning of carrying capacity. Utilized resource that exceeds available resource is used as a transgression indicator with regard to the resource implication of CCE. The environmental implication of CCE relates to the threshold of assimilative capacity of the aquatic and atmospheric environment for waste discharged. The transgression indicator can be simply either the waste discharge in excess of the environmental assimilative capacity or the local environmental quality above a prescribed standard. The ecological implication of CCE corresponds to the ecosystem services available to benefit the human population of a given area, and derives from the local habitat, biological, and systemic characteristics of the ecosystem. Here, the transgression indicator could be estimated from the excess of demand over supply of ecosystem services. Social implication of CCE is the ability of human society to enhance the available resource, environmental assimilative capacity, and ecosystem services by technological and financial means, limited to a specific spatial and temporal environment. Here, the excess of demand over supply of technology and funding is regarded at the transgression indicator for social CCE related to a specific human society. 2.3. New components of CCE The present study considers four components derived from the concept and implications of CCE, namely: natural resources capacity, environmental assimilative capacity, ecosystem services capacity, and society supporting capacity. The components concerned with natural capital (i.e. natural resources, environmental assimilative capacity, and ecosystem services) directly influence CCE. However, the social component also affects CCE by altering the other three components. Moreover, the natural capital components are not independent; for example, water assimilative capacity is determined by availability of water resource. Fig. 1 provides
2.2. Reconsideration of the concept and implication of CCE Carrying Capacity of the Environment (CCE) is concerned with the natural environment, and should also include perceptual carrying capacity and institutional carrying capacity (Godschalk and Parker, 1975). CCE is the limit at which human activity will lead to undesirable changes to the environment, assuming there are certain limits the environment itself imposes on development. CCE therefore has three components: ecological capacity; environmental assimilative capacity; and renewable resources capacity (Godschalk and Parker, 1975). However, environmental capacity does not solely involve natural resources and environmental assimilative capacity. Instead, the environment also encompasses natural disasters, geological systems, and other natural phenomena. The concept of CCE should emphasize ecological aspects of the environment (including natural resources, environmental assimilative capacity, and ecosystem services), which are addressed in the majority of SEA and environmental planning decisions in China. Herein, a more specific definition of CCE is proposed as the combined threshold in time and space of natural resources, environmental assimilative capacity, ecosystem services, and social supporting capacity of the environment that could carry socio-economic activities without causing obvious changes or damage to structures and functions of the environment. Environmental problems occur mostly because Environmental Stress (ES) imposed by human socio-economic activities transgresses the CCE, hence causing the environment to be damaged or malfunction. The above definition also means that CCE has resource,
Natural resources capacity
Society supporting capacity Ecosystem
Env.
services
assimilative
capacity
capacity
Carrying Capacity of the Environment
Fig. 1. Four components of CCE.
R.Z. Liu, A.G.L. Borthwick / Journal of Environmental Management 92 (2011) 2047e2053
a schematic illustration of the interdependent relationships of the four components of CCE. Natural resources capacity is the primary basic function of the environment in terms of supplying resources to human society, and reflects the proper level or total quantity of natural resources explored or consumed in a sustainable way. Local land resource and water resource are finite and sensitive to development, and so are usually considered by SEA, environmental planning and management. Energy resource is readily transferable and so is not incorporated in the local natural resources capacity. Therefore, the available water resource and suitable construction land resource are used herein to measure the natural resources capacity in CCE. Environmental assimilative capacity reflects the wastecontainment capacity of receiving waters and the atmosphere by the dispersal, transport, and treatment of waste. Water assimilative capacity and atmospheric assimilative capacity are separately accounted for when measuring environmental assimilative capacity in CCE. The ecosystem services capacity places particular emphasis on regulating, supporting, and cultural services, which are determined according to the ecosystem characteristics (e.g. category, and area). Alternative measurement indicators of ecosystem services include the value of biome services (Costanza et al., 1997), the Leaf Area Index (LAI) (Wang and Wang, 2004), the value of different land use types (Ran et al., 2006), and the area of ecological land (e.g. forest, wetland, or nature reserve). Herein Sum LAI and forest area have been adopted to measure the ecosystem services capacity in CCE. Society supporting capacity is an exogenous variable that affects CCE by changing its endogenous variables, the natural resources capacity, environmental assimilative capacity, and ecosystem services capacity. As the most active and manageable variable, the society supporting capacity is measured using Gross Domestic Product (GDP) per capita and proportion of total GDP invested in environmental protection. 2.4. Measuring CCE In summary, we select the following eight measurable indicators of CCE: available water resource, suitable construction land resource, water assimilative capacity, atmospheric assimilative capacity, Sum LAI, forest area, GDP per capita, and proportion of total GDP invested in environmental protection. The indicators of forest area, GDP per capita, and proportion of total GDP invested in environmental protection are directly derived from local statistical data. Sections 2.4.1e2.4.5 describe the methodologies by which the indicators are estimated. 2.4.1. Available water resource Available water resource is taken to be the maximum quantity of water that can be abstracted without an adverse spatial or temporal change occurring to the environment. Available surface water, available ground water, water intake, and wastewater reclamation are included in the measurement of available water resource from
WAR ¼ WAS þ WAG þ WI þ WWR WRC
(1)
where WAR is available water resource, WAS is available surface water, WAG is available ground water, WI is water transferred in, WWR is wastewater reclamation, and WRC is water counted both as available surface water and available ground water. 2.4.2. Suitable construction land resource Construction land resource is used for industrial production, infrastructure, recreational services, etc. Herein, suitable construction land resource is assigned as the measure of land supply for
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construction that should not impact adversely on a specific environment. This measure accounts for both suitable and less suitable land areas estimated through ecological assessment, whereby landform and land cover factors related to ecological suitability are mapped and overlaid according to different weights using GIS tools. Here, the suitability value for a land unit is estimated from
8 Cij ¼ 0 > <0 n P Ci ¼ Wj Cij Cij s 0; i ¼ 1; 2; .; m; j ¼ 1; 2; .; n > :
(2)
j¼1
where Ci is the suitability value of the i-th land unit, Cij is the suitability of the j-th factor in the i-th land unit, and Wj is the weight of the j-th factor. Land units are ranked according to whether construction is forbidden, limited, less suitable, or suitable. The combined area of less suitable construction land and suitable construction land is taken to be the suitable construction land resource. 2.4.3. Water assimilative capacity Water assimilative capacity refers to the ability of a body of water to carry waste without adverse effects on the environment or on the users of its resources. Water assimilative capacity is limited by the hydrodynamic and biological characteristics of the water body (Tett et al., 2007), water quality targets, and characteristics of pollutants and their discharge (Zhang and Liu, 1991). A water quality model is used to determine the water assimilative capacity, (Novotny and Krenkel, 1975), with a one-dimensional model generally applied to most water bodies, except for large, wide rivers where a two-dimensional model is often used. The details are set out in the China Technical Guide to Water Assimilative Capacity Determination (CAEP, 2003). In the present study, the water quality control section is set at a distance equal to 40% of the length of a given river reach, measured from the start of the reach. The water assimilative capacity is not single-valued but has a range of values that can alter according to the river discharge characteristics. A linear planning model is used to determine the maximum water assimilative capacity. 2.4.4. Atmospheric assimilative capacity Atmospheric assimilative capacity is defined as the maximum emission load that a region can assimilate without the air quality of the region deteriorating below a given threshold. Atmospheric assimilative capacity depends on a variety of environmental parameters, including meteorological conditions, terrain characteristics, and emission characteristics (see e.g. Goyal and Chalapati Rao, 2007). Various approaches are described in the literature for estimating the atmospheric assimilative capacity of a region. Goyal et al. (2006) propose two approaches, one based on a ventilation coefficient, the other through pollution potential. SEPA (2003) recommend an A-P value method and multi-source simulation model to estimate atmospheric assimilative capacity in China. However, the A-P value method is based on a box model using a ventilation coefficient, and is unable to provide a specific assimilative capacity as it does not incorporate terrain and emission characteristics. Alternatively, the multi-source simulation model (used herein) provides an estimate of atmospheric assimilative capacity based on air quality modeling which takes into consideration region-specific meteorological conditions, terrain characteristics, and emission loads from different sources. Following Goyal and Chalapati Rao (2007), the discharged emission load at which the maximum allowable concentration is reached under predefined critical conditions is taken to be the assimilative capacity of the region. Prediction of ground-level concentrations of pollutants is
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Table 1 Average LAI of biome/land cover type (m2/m2). Biome/Land cover
Farmland
Garden
Woodland
Grassland
Wetland
Water
Construction land
Other land
Average LAI
3.0
3.0
5.0
2.0
6.5
0
0.5
1.0
carried out using the US EPA approved ISCST-3 simulation model (EPA, 1995a, 1995b). It should be noted that the atmospheric assimilative capacity has a range of values, depending on the variation of emission characteristics with given meteorological and topographical conditions. The maximum value is determined using a linear planning model. 2.4.5. Sum LAI In the measurement framework of CCE, the ecosystem services focus on regulating, supporting, and cultural services. Therefore ecological capacity (Wackernagel and Rees, 1996) expressed by area of production land is not suitable for the measurement of ecosystem services capacity. Also emergy (Odum, 1987), value of biome services (Costanza et al., 1997), and value of different land use types (Ran et al., 2006) are not adopted because they would not provide a comparable estimate of the difference between supply and demand of ecological services. LAI is broadly defined as the amount of leaf area in a vegetation canopy per unit land area. Like net primary productivity, LAI is a key structural characteristic of vegetation and land cover because of the role of green leaves in a wide range of biological and physical processes (Scurlock et al., 2001), which dominates the function of ecosystem services in terms of land cover type and biome. Sum LAI, i.e. the sum of average LAI for all land cover types, is used to measure the difference between ecosystem services capacity (supply) and expectation (demand) in a region (Wang and Wang, 2004). Scurlock et al. (2001) compiled LAI data for 1008 samples obtained from more than 400 sites worldwide during the period 1932e2000, and summarized the averaged LAI for each of 15 main biomes/land cover types. Table 1 lists the averaged LAI for China obtained for different types of biome/land cover (see Costanza et al., 1997; Ran et al., 2006). The sum LAI is determined as follows: (1) The type of biome/land cover is identified by interpreting either remote sensing images or land use/land cover maps, counting the area ratio wi of the i-th biome to land cover type in a given region. (2) Sum LAI is then estimated from
LS ¼
n X
wi Li
(3)
i¼1
Here, LS is sum LAI in a given region, m2/m2, Li is average LAI of the i-th biome/land cover type determined from Table 1, m2/m2, and wi is the area ratio of the i-th biome to land cover type in the given region. (3) Set expectation of sum LAI. It is difficult to provide an exact expected value of sum LAI at the present day. However, by progressively increasing the sum LAI, the ecosystem services expand to meet the growing demand. Herein, the expectation of sum LAI in 2010, 2020, and 2050 is respectively set equal to 3, 4, and 5 m2/m2, the values based on the assumption that biome with high LAI will cover most of the land area in 2050. Assessment of the carrying state of ecosystems services is conducted by comparing the supply and expectation of sum LAI.
2.5. Assessment of CCE CCE assessment indicates to what degree CCE is transgressed by ES due to human disruption, and so provides very important scientific information to decision-makers. CCE assessment involves a set of comparable supply (CCE) and demand (ES) indexes, with the former being the threshold of the latter. The main technique to assess CCE involves comparing these paired indicators, making judgments as to whether the environment is capable of carrying or not, and then determining the degree of carrying or transgressing. 2.5.1. Indexes of assessing CCE Table 2 shows the three-layer index system used to assess CCE. In the objective layer, the CCE index is a comprehensive variable with four component indexes located in the middle layer. Each component index is derived from several basic indexes in the primary layer. The overall CCE index is denoted by c, with each component index denoted by ci, where i is 1, 2, 3 or 4.In the primary layer, each CCE basic index cij is paired with an ES basic index pij, where j is the respective sub index for the i-th component index. 2.5.2. Assessment of the basic indexes Once values of the paired basic indexes have been determined, assessment of the basic indexes is carried out using the carrying capacity surplus ratio dij defined as
Table 2 Assessment index system of CCE. Objective (c)
Middle (ci)
Primary CCE basic index (cij)
ES basic index (pij)
Unit
CCE
Natural resources capacity
Available water resource Suitable construction land resource Assimilative capacity of SO2 Assimilative capacity of NO2 Assimilative capacity of PM10 Assimilative capacity of COD Assimilative capacity of NH4eN Forest area Sum LAI GDP per capita Proportion of total GDP invested in environmental protection
Water consumption Construction land Emission of SO2 Emission of NO2 Emission of PM10 COD discharge NH4eN discharge Planned forest area Target Sum LAI Target GDP per capita Target proportion of total GDP invested in environmental protection
t/a km2 t/a t/a t/a t/a t/a km2 m2/m2 Yuan %
Environmental assimilative capacity
Ecosystem services capacity Society supporting capacity
R.Z. Liu, A.G.L. Borthwick / Journal of Environmental Management 92 (2011) 2047e2053
dij ¼
cij pij pij ¼ 1 cij cij
(4)
where cij is the CCE basic index, and pij is the ES basic index. The principle of assessment is the following. For dij > 0, the environment is capable of carrying stress due to human interference, and dij provides an estimate of the degree of surplus capacity. For dij < 0, the stress transgresses CCE, with dij representing the degree of transgression. For dij ¼ 0, when cij ¼ pij, the stress of human interference has reached the carrying capacity threshold, and no more stress should be placed on this index. 2.5.3. Assessment of the CCE index and its component indexes The CCE index may be regarded as a vector with four components, and the component index as a sub-vector with several basic indexes. A vector of surplus ratio of carrying capacity is proposed to assess the CCE index and its component indexes, the idea translated from vector assessment of regional carrying capacity (Yu and Mao, 2002). For component index assessment, we define the surplus ratio of the i-th component index as
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u X u 1 ni 2 pij Di ¼ 1 t r ; rij ¼ cij ni j ¼ 1 ij
(5)
where ni is the number of sub indexes of the i-th component index, and rij is the ratio of the ES basic index to the ECC basic index. Three states of carrying capacity in the component index are assessed for Di > 0, Di ¼ 0, and Di < 0, with the degree of carrying or transgressing represented by the value of Di. For assessment purposes, the surplus ratio of the CCE index, D, is obtained from
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u m u1 X D ¼ 1t ð1 Di Þ2 m
(6)
i¼1
where m is the number of sub components (equal to 4 in the present study). In keeping with the previous definitions, D represents the degree to which the environment carries stress. For D > 0, the environment is fully capable of carrying the stress induced by human interference, whereas for D < 0, the stress transgresses the CCE. 3. Results 3.1. Measurement of CCE in 2005 and 2010 Data on available surface water, available ground water, and double-counted water were gained from local detailed water resource reports (unpublished). Data on wastewater reclamation were obtained from published statistics for 2005 (Ningbo Bureau of Statistics, 2006), and from predictions for 2010 assuming 20% wastewater. It was also assumed that no water was transferred into or out of Ningbo. Table 3 lists the values of available water resources in Ningbo for 2005 and the predictions for 2010. The factors used to determine ecological suitability included drinking water source protection area, natural conservation area, volume of water body, land cover, fracture zone, mean gradient,
and traffic convenience (obtained using GIS). Suitability values were derived from overlays of the above factors according to Equation (2) using GIS tools. Land with a suitability value more than 4.6 was ranked as ‘suitable or less suitable’. The resulting total area of suitable construction land resource was 1728 km2 in Ningbo. One-dimensional numerical models recommended by CAEP (2003) were used to simulate the water quality of inland rivers and tidal river segments, and hence evaluate the water assimilative capacity for COD and NH4eN. The models considered a total of 36 river segments related to the Yaojiang River, Fenghuajiang River, and Yongjiang River. Model input included the start and end locations, flow volume, flow velocity, length, objective water quality, present water quality, and degradation coefficient for each section. Further input related to sewage discharge into the rivers included outlet position, discharge volume and velocity, and concentrations of COD and NH4eN. Maximum allowable discharge loads, i.e. assimilative capacity for COD and NH4eN, were summed to 13,440 t and 1211 t by running the models for all 36 segments of Ningbo. The ISCST-3 model was used to evaluate atmospheric assimilative capacity. Emission data were based on an emission declaration system and environment statistics, both provided by the local environmental protection bureau. Meteorological data at hourly intervals were collected by a local weather station. Receptor data included information from Ningbo Middle School, Ningbo College, Ningbo Fourth Middle School, and Longsai Hospital. Control conditions were set as default. Predictions have been made of the mean hourly ground-level concentrations of SO2, NO2, and PM10 pollutants at four receptors in 2005. Table 4 lists the predicted and measured mean annual concentrations, and API values derived from the mean hourly ground-level concentration data. As a result, the predicted and monitored numbers of days with API >100 were very close or equal to the criterion. This implies that emissions in 2005 may be equated to the allowable emissions, i.e. the atmospheric assimilative capacity for the given spatial distribution of emission sources. In this case, the atmospheric assimilative capacities of the SO2, NO2, and PM10 pollutants were 1.99 105, 1.62 105, and 4.76 104 t, respectively. The area of each biome/land cover type was derived using GIS tools from the vector map of land use derived from the annuallyupdated land records for 2005. The Sum LAI for 2005 was estimated to be 3.47 m2/m2 using Equation (3). For 2010, Sum LAI was predicted as 3.46 m2/m2, based on prediction of land use structure. From the local statistics, the estimated forest area was 4682.5 km2 in 2005; this value was unchanged in 2010, and is expected to remain the same for at least the near future. In 2005, the residential population of Ningbo was 6.136 million, with a GDP per capita of 38,733 RMB. Allowing for local development, the GDP per capita in 2010 is estimated to be 61400 RMB. The environmental protection investment rate was 2.96% GDP in 2005 according to local statistics. Using the local planning report (unpublished), the predicted value for 2010 is 3.02%.
3.2. Assessment of CCE in 2005 and 2010 In the calculation of CCE for 2005 and 2010, the value of ES for 2005 was derived from statistical data and that of ES for 2010 was Table 4 Predicted and monitored mean annual concentrations of atmospheric pollutants for Ningbo in 2005.
Table 3 Available water resources in Ningbo (unit: 108 t).
2005 2010
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Available surface water
Available ground water
Double-counted water
Wastewater reclamation
Available water resources
25.58 25.58
17.10 17.10
15.23 15.23
0.11 1.77
27.56 29.22
Predicted Monitored Criteria
SO2 (mg/m3)
NO2 (mg/m3)
PM10 (mg/m3)
Number of days API > 100 (d)
0.049 0.047 0.06
0.065 0.066 0.08
0.089 0.081 0.10
31 35 35
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predicted according to the Ningbo 11th National Economic and Social Development Plan. Supplementary Table 1 lists the resulting values of CCE and ES. The CCE basic indexes listed in Supplementary Table 2 were assessed using the carrying capacity surplus ratio model based on the values of the corresponding pairs of CCE and ES indexes. The results in Supplementary Table 2 indicate the following:
The following three prerequisites should be met. (1) Strict total quantity control of pollutants is required, with SO2 and COD reduced by 48% and 15% from the 2005 levels. (2) Improved management and technology should be used to reduce resource consumption and pollutant discharge. (3) Limits should be placed on population and economic goals. 4. Discussion
(1) The available water resources could carry water consumption, having a net surplus abundance that decreases from 27% in 2005 to 12% in 2010. (2) The land can support further construction, given the net surpluses of 24% in 2005 and 15% in 2010. (3) Water bodies were unable to carry the pollutant discharges of COD and NH4eN in 2005, as is evidenced by the respective shortages of 65% and 55% in assimilative capacity. And the shortages are predicted to decrease to 30% and 50% in 2010 respectively. Severely polluted rivers include the Fenghuajiang River and stagnant reaches on the Ningbo plain. (4) The atmospheric assimilative capacity was fully laden in 2005, when the number of days with API 100 decreased to the critical value of 330. It is predicted that the emission of SO2 will be reduced by 58% in order to achieve the required emission target in 2010. Even so, the emissions of NO2 and PM10 are estimated to exceed their assimilative capacities by 23% and 30% respectively in 2010. (5) The environment could supply the local inhabitants with sufficient ecosystem services. Forest area had a net surplus of 27% in both 2005 and 2010, and similarly the sum LAI was in surplus by 14% in 2005 and 13% in 2010. (6) GDP per capita and the resulting environmental protection investment were both insufficient to support improvement of the local environment in 2005. However, the GDP per capita rose considerably by 2010, helping reduce the shortage in environmental protection investment to 16% of GDP. The vector of surplus ratios of carrying capacity is next used to assess the CCE index and its component indexes. Fig. 2 indicates the carrying state for Ningbo, whose environmental stresses transgressed CCE by 2% in 2005, primarily because of pollutants overloading the local assimilative capacities. By 2010 however, it appears that the environment could carry the stresses from human development given a 3% abundance of CCE owing to societal support and the implementation of pollution mitigation measures.
Whole carrying state
0.5
Society supporting
0
Natural resources
-0.5
Ecosystem services
Assimilative capacity
2005
2010
Fig. 2. Assessment of ECC and its component indexes for Ningbo in 2005 and 2010.
A new definition of CCE has been proposed based on four components related to resource, environment, ecology, and society. These components are quantified in a way that distinguishes between ES and CCE, and clarifies the degree to which surplus or transgression occurs. The environment involves natural resources, assimilative capacity, and ecosystem services, all of which can be changed by human society. In practice, SEA and environmental planning deal with all four aspects of the environment. Thus the present method provides a systemic, straightforward basis for the measurement and assessment of CCE and its four components. However, the four key indictors selected herein to describe CCE are not comprehensive and further indicators such as energy supply and soil assimilative capacity may be added in a future study. The case study of Ningbo demonstrates the model is useful in practice, though further work is needed to improve the representation of ecosystem services (given the difficulty encountered in assessing the correct match of demand to supply). A carrying capacity surplus ratio model has been used to assess basic indexes, and a vector of surplus ratio of carrying capacity model established for integrated indexes. The former model was designed to compare directly the CCE and ES basic indexes. This provides a convenient and accurate judgment as to whether transgression occurs, and a measure of the degree to which the threshold of each basic index is either transgressed or exceeded. The latter model calculates the Euclidean vector of surplus ratios instead of linear plus. The integrated assessment inherently incorporates the nonlinear relationships between a vector and its sub-vectors, avoiding inaccuracy from the conventional linear plus method and its subjective weights. Both models have also been applied to the case study for Ningbo, demonstrating their capability for quantitative assessment of CCE and its basic indexes in practice. However, it should be noted that considerable effort was required to prepare the database, carry out model predictions, and determine the basic indexes, before obtaining the CCE index for Ningbo. In practice, it may be sensible to carry out an auxiliary assessment in relatively straightforward cases where a quick assessment is required at low cost. Qualitative assessment of CCE should be performed by comparing indicators of environmental quality and ecological quality, which are regularly monitored (e.g. mean annual concentration of pollutants or vegetation cover ratio), according to prescribed criteria, instead of comparing ES basic indexes with CCE basic indexes. 5. Conclusions A comprehensive measurement system for CCE has been proposed. It is based on a new definition of CCE and comprises measurable models for natural resources supply, environmental assimilative capacity, ecosystem services supply, and society supporting capacity. The measurement system is useful and applicable because it covers the full dimensions of CCE, and includes models for suitable construction land resource and ecosystem services in addition to other more established models. The index system for assessment of CCE has been designed to correspond to the measurement system. A carrying capacity surplus ratio model and a vector of surplus ratio of carrying capacity model are respectively
R.Z. Liu, A.G.L. Borthwick / Journal of Environmental Management 92 (2011) 2047e2053
proposed to assess the basic index states and the integrated index state for CCE. The assessment models rely on a direct comparison of CCE and ES for each basic index, use a Euclidean vector for integration instead of linear plus, and thus produce convenient, accurate, and quantitative assessment results. The case study of Ningbo has demonstrated the assessment of CCE in practice. In 2005, Ningbo’s environmental stress transgressed CCE by 2%. Local water bodies were unable to carry pollutant discharges of COD and NH4eN, the shortfalls being 65% and 55% of assimilative capacity. The GDP per capita and environmental protection investment in GDP also undershot their respective thresholds by 16% and 18%. In 2010, however, the situation has changed, with the environment apparently able to carry further stress from human development (given a 3% abundance of CCE) by enhanced societal support and pollution mitigation. Acknowledgments This research was supported by the National Natural Science Foundation of China under Grant No. 40801229 and the National High Technology Research and Development Program of China under Grant No. 2007AA06A404. The authors are grateful to Prof. Hao Jiming and Prof. Wang Chengwen of Tsinghua University, and Ningbo Environmental Protection Bureau for their assistance regarding the case study of Ningbo. Appendix. Supplementary information Supplementary data related to this article can be found online at doi:10.1016/j.jenvman.2011.03.033. References Arrow, K., Bolin, B., Costanza, R., Dasgupta, P., Folke, C., Holling, C.S., Jansson, B.O., Levin, S., Mäler, K.G., Perrings, C., Pimentel, D., 1995. Economic growth, carrying capacity, and the environment. Science 268, 520e521. Baldwin, J.H., 1985. Environmental Planning and Management. Westview Press, Boulder. Bartels, G.B., Norton, B.E., Perier, G.K., 1993. An examination of the carrying capacity concept. In: Behnke Jr., R.H., Scoones, I., Kerven, C. (Eds.), Range Ecology at Disequilibrium. Overseas Development Institute, London, pp. 89e103. Chinese Academy for Environmental Planning (CAEP), 2003. China Technical Guide of Water Assimilative Capacity Determination (in Chinese). Clarke, A.L., 2002. Assessing the carrying capacity of the Florida Keys. Population and Environment 23, 405e418. Costanza, R., d’Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’Nell, R.V., Raskin, R.G., Stutton, P., van den Belt, M., 1997. The value of the world’s ecosystem services and natural capital. Nature 387, 253e260. Daily, G.C., Ehrlich, P.R., 1996. Socioeconomic equity, sustainability, and Earth’s carrying capacity. Ecological Applications 6, 991e1001. EPA2454 /B2952003a, 1995a. User’s Guide for the Industria1 Source Complex (ISC3) Dispersion Models. In: User Introductions, vol. I. US EPA, Washington. EPA2454 /B2952003b, 1995b. User’s Guide for the Industria1 Source Complex (ISC3) Dispersion Models. In: Description of Model Algorithms, vol. II. US EPA, Washington. Godschalk, D.R., Parker, F.H., 1975. Carrying capacity: a key to environmental planning. Journal of Soil and Water Conservation 30, 160e165.
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Goyal, P., Anand, S., Gera, B.S., 2006. Assimilative capacity and pollutant dispersion studies for Gangtok city. Atmospheric Environment 40, 1671e1682. Goyal, S.K., Chalapati Rao, C.V., 2007. Air assimilative capacity-based environment friendly sitting of new industries: a case study of Kochi region, India. Journal of Environmental Management 84, 473e483. Hardin, G., 1986. Cultural carrying capacity: a biological approach to human problems. BioScience 36, 599e604. Ng, K.L., Obbard, J.P., 2004. Strategic environmental assessment in Hong Kong. Environment International 31, 483e492. Ningbo Bureau of Statistics, 2006. Ningbo Statistical Yearbook 2006. China Statistics Press, Beijing (in Chinese). Novotny, V., Krenkel, P.A., 1975. A waste assimilative capacity model for a shallow, turbulent stream. Water Research 9 (2), 233e241. Odum, H.T., 1987. Ecology and Economy, Emergy Analysis and Environmental Decision Making. John Wiley & Sons, Inc., New York & Toronto. Oh, K., Jeong, Y., Lee, D., Lee, W., Choi, J., 2005. Determining development density using the urban carrying capacity assessment system. Landscape and Urban Planning 73, 1e15. Papageorgiou, K., Brotherton, I., 1999. A management planning framework based on ecological, perceptual and economic carrying capacity: the case study of Vikos-Aoos National Park, Greece. Journal of Environmental Management 56, 271e284. Prato, T., 2009. Fuzzy adaptive management of social and ecological carrying capacities for protected areas. Journal of Environmental Management 90, 2551e2557. Ran, S.H., Lv, C.H., Jia, K.J., Qi, Y.H., 2006. Environmental impact assessment of the land use change in China based on ecosystem service value. Environmental Sciences 27 (10), 2139e2144 (in Chinese). Rees, W., 1992. Ecological footprints and appropriated carrying capacity: what urban economics leaves out. Environment and Urbanization 4, 121e130. Saveriades, A., 2000. Establishing the social tourism carrying capacity for the tourist resorts of the east coast of the Republic Cyprus. Tourism Management 21 (2), 147e156. Scurlock, J.M.O., Asner, G.P., Gower, S.T., 2001. Worldwide Historical Estimates and Bibliography of Leaf Area Index, 1932e2000. ORNL Technical Memorandum TM-2001/268, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A. Seidl, I., Tisdell, C.A., 1999. Carrying capacity reconsidered: from Malthus’ population theory to cultural carrying capacity. Ecological Economics 31, 395e408. SEPA HJ/T131-2003, 2003. Technical Guidelines for Environmental Impact Assessment of Development Area. R.P. China SEPA, Beijing (in Chinese). Tang, J.W., Ye, W.H., 1998. Study on environmental carrying capacity and its quantification. China Environmental Sciences 18 (3), 227e230 (in Chinese). Tett, P., Portilla, E., Inall, M., Gillibrand, P., Gubbins, M., Amundrod, T., 2007. Modelling the Assimilative Capacity of Sea-Lochs, the Final Report on SARF 012. Thompson, S., Treweek, J.R., Thurling, D.J., 1995. The potential application of strategic environmental assessment (SEA) to the farming of Atlantic Salmon (Salmo salar L.) in Mainland Scotland. Journal of Environmental Management 45, 219e229. Wackernagel, M., Rees, W., 1996. Our Ecological Footprint: Reducing Human Impact on the Earth. New Society Publishers, Gabriola Island. Wang, J.J., Yao, X.H., Li, J.R., Chang, H., Wang, Y.G., 2000. Assessment for ecological carrying capacity of Heihe river basin. Research of Environmental Sciences 13 (2), 44e48 (in Chinese). Wang, R.S., Wang, X.R., 2004. Research on Ecosystem Service Function of Urban Living and Developing Environment. China Meteorological Press, Beijing (in Chinese). Ye, W.H., 1992. Theories of environmental carrying capacity and its scientific implications. Researches on Environmental Sciences 5 (S1), 108e111 (in Chinese). Yu, D.L., Mao, H.Y., 2002. Regional carrying capacity: case studies of Bohai Rim area. Journal of Geographical Sciences 12 (2), 177e185. Zeng, W.H., Wang, H.D., Xue, J.Y., Ye, W.H., Guan, B.R., Mei, F.Q., 1991. Environmental carrying capacity: a key to the coordination of the development of population, resources and environment. China Population. Resources and Environment 1 (2), 33e37 (in Chinese). Zhang, Y.L., Liu, P.Z., 1991. A General Handbook of Water Environmental Capacity. Tsinghua University Press, Beijing (in Chinese).
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Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman
Measurement and assessment of carrying capacity of the environment in Ningbo, China R.Z. Liu a, *, Alistair G.L. Borthwick b a
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China b Department of Engineering Science, University of Oxford, Parks Rd., Oxford OX1 3PJ, UK
a r t i c l e i n f o
a b s t r a c t
Article history: Received 5 October 2010 Received in revised form 19 February 2011 Accepted 24 March 2011 Available online 19 April 2011
Carrying Capacity of the Environment (CCE) provides a useful measure of the sustainable development of a region. Approaches that use integrated assessment instead of measurement can lead to misinterpretation of sustainable development because of confusion between Environmental Stress (ES) indexes and CCE indexes, and the selection of over-simple linear plus models. The present paper proposes a comprehensive measurement system for CCE which comprises models of natural resources capacity, environmental assimilative capacity, ecosystem services capacity, and society supporting capacity. The corresponding measurable indexes are designed to assess CCE using a carrying capacity surplus ratio model and a vector of surplus ratio of carrying capacity model. The former aims at direct comparison of ES and CCE based on the values of basic indexes, and the latter uses a Euclidean vector to assess CCE states. The measurement and assessment approaches are applicable to Strategic Environmental Assessment (SEA) and environmental planning and management. A case study is presented for Ningbo, China, whereby all the basic indexes of ECC are measured and the CCE states assessed for 2005 and 2010. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Carrying capacity Measurement Strategy environmental assessment Environmental planning Ningbo
1. Introduction The term carrying capacity was coined in the late 1890s by range managers concerned with the use of land for grazing livestock (see e.g. Bartels et al., 1993). In the 1970s, Godschalk and Parker (1975) explored the use of three types of environmental, institutional, and perceptual carrying capacity in natural and man-made systems. Subsequently, environmental carrying capacity became a valuable tool for environmental planning and management (Baldwin, 1985; Zeng et al., 1991; Ye, 1992). Carrying capacity has also been called ecological capacity (Rees, 1992; Wackernagel and Rees, 1996), ecological resilience (Arrow et al., 1995), and ecological carrying capacity (Wang et al., 2000; Prato, 2009), when applied to local, regional, and urban systems (Yu and Mao, 2002; Oh et al., 2005). Carrying capacity has also evolved into social carrying capacity (Daily and Ehrlich, 1996), cultural carrying capacity (Hardin, 1986; Seidl and Tisdell, 1999), and tourism carrying capacity (Saveriades, 2000; Prato, 2009). However, carrying capacity remains a highly elusive concept and its implementation is
* Corresponding author. Tel.: þ86 010 59893106; fax: þ86 010 59893086. E-mail address: [email protected] (R.Z. Liu). 0301-4797/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2011.03.033
hindered by practical problems involved in its measurement (Papageorgiou and Brotherton, 1999). The hypothetical counting of natural resources, environmental quality standards for air and water, and socio-economic statistics cannot provide an accurate, comprehensive measure of carrying capacity (see e.g. Tang and Ye, 1998; Yu and Mao, 2002). In practice, carrying capacity is often estimated by comparing stress on the environment (e.g. demand of natural resources or ecological footprint) against environmental thresholds (e.g. available natural resources or ecological capacity) (see e.g. Wackernagel and Rees, 1996; Tang and Ye, 1998; Yu and Mao, 2002; Clarke, 2002; Oh et al., 2005). But most of these conventional assessments do not provide correct results because they misrepresent the stress, state, and threshold of the environment. Bearing in mind this experience, the present paper focuses on the Carrying Capacity of the Environment (CCE), which provides a powerful tool for Strategic Environmental Assessment (SEA) (Thompson et al., 1995; Ng and Obbard, 2004) and environmental planning and management (Godschalk and Parker, 1975; Baldwin, 1985). A new definition of CCE is made, noting future use and remediation of the environment. Next, a specific, comprehensive measurement of CCE for a certain region is proposed, and an integrated assessment of CCE (namely the vector-surplus ratio of carrying capacity model based on stress and carrying capacity) is developed.
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2. Materials and methods 2.1. Study area As a major deep-water port for foreign trade, Ningbo has become an important industrial and economic center in Zhejiang Province, China. Ningbo is located in the middle of the eastern seaboard of mainland China, to the South of the Yangtze River Delta (see Supplementary Fig. 1). Zhejiang Province has a subtropical monsoon climate, characterized by mild temperature, moderate humidity and distinct seasons. Hills and mountains occupy more than 50% of the land area. Three major rivers flow through the plains of Ningbo: the Yaojiang River, the Fenghuajiang River, and the Yongjiang River. Ningbo occupies a total land area of 9695 km2, and comprises six districts (Haishu, Jiangdong, Jiangbei, Zhenhai, Beilun and Yinzhou), three county-level cities of Yuyao, Cixi and Fenghua, and two counties of Xiangshan and Ninghai. In 2005, the total population of Ningbo was 5.57 million, of whom 1.83 million resided in urban areas. Its economic development is based on advanced manufacturing, petrochemical, energy, iron and steel, papermaking, shipbuilding, and service industries. In 2005, the gross domestic product of Ningbo was 245 billion RMB, and its industrial surplus was 135 billion RMB. However, this tremendous economic achievement has placed a heavy burden on the environment of Ningbo. In 2005, the concentration of sulfur dioxide in the air reached 0.047 mg/m3, close to the National Secondary Standard of 0.060 mg/ m3. The Air Pollution Index (API) indicated that air pollution levels harmful to human health occurred on 35 days in 2005. Water was severely polluted, with high concentrations of COD in urban waters and stagnant rivers. The average water resource available per annum per person in Ningbo was a mere 1285 m3, far below the average of 2100 m3 for Zhejiang Province. Land available for building development became scarce, exacerbated by the amount of land already taken for agrarian and industrial development. The local ecosystem was damaged as forests and beach wetlands were replaced by land development projects.
environmental, ecological and social implications. The resource implication of CCE relates to the threshold of available natural resources for human demand in the environment, which is the original, primary meaning of carrying capacity. Utilized resource that exceeds available resource is used as a transgression indicator with regard to the resource implication of CCE. The environmental implication of CCE relates to the threshold of assimilative capacity of the aquatic and atmospheric environment for waste discharged. The transgression indicator can be simply either the waste discharge in excess of the environmental assimilative capacity or the local environmental quality above a prescribed standard. The ecological implication of CCE corresponds to the ecosystem services available to benefit the human population of a given area, and derives from the local habitat, biological, and systemic characteristics of the ecosystem. Here, the transgression indicator could be estimated from the excess of demand over supply of ecosystem services. Social implication of CCE is the ability of human society to enhance the available resource, environmental assimilative capacity, and ecosystem services by technological and financial means, limited to a specific spatial and temporal environment. Here, the excess of demand over supply of technology and funding is regarded at the transgression indicator for social CCE related to a specific human society. 2.3. New components of CCE The present study considers four components derived from the concept and implications of CCE, namely: natural resources capacity, environmental assimilative capacity, ecosystem services capacity, and society supporting capacity. The components concerned with natural capital (i.e. natural resources, environmental assimilative capacity, and ecosystem services) directly influence CCE. However, the social component also affects CCE by altering the other three components. Moreover, the natural capital components are not independent; for example, water assimilative capacity is determined by availability of water resource. Fig. 1 provides
2.2. Reconsideration of the concept and implication of CCE Carrying Capacity of the Environment (CCE) is concerned with the natural environment, and should also include perceptual carrying capacity and institutional carrying capacity (Godschalk and Parker, 1975). CCE is the limit at which human activity will lead to undesirable changes to the environment, assuming there are certain limits the environment itself imposes on development. CCE therefore has three components: ecological capacity; environmental assimilative capacity; and renewable resources capacity (Godschalk and Parker, 1975). However, environmental capacity does not solely involve natural resources and environmental assimilative capacity. Instead, the environment also encompasses natural disasters, geological systems, and other natural phenomena. The concept of CCE should emphasize ecological aspects of the environment (including natural resources, environmental assimilative capacity, and ecosystem services), which are addressed in the majority of SEA and environmental planning decisions in China. Herein, a more specific definition of CCE is proposed as the combined threshold in time and space of natural resources, environmental assimilative capacity, ecosystem services, and social supporting capacity of the environment that could carry socio-economic activities without causing obvious changes or damage to structures and functions of the environment. Environmental problems occur mostly because Environmental Stress (ES) imposed by human socio-economic activities transgresses the CCE, hence causing the environment to be damaged or malfunction. The above definition also means that CCE has resource,
Natural resources capacity
Society supporting capacity Ecosystem
Env.
services
assimilative
capacity
capacity
Carrying Capacity of the Environment
Fig. 1. Four components of CCE.
R.Z. Liu, A.G.L. Borthwick / Journal of Environmental Management 92 (2011) 2047e2053
a schematic illustration of the interdependent relationships of the four components of CCE. Natural resources capacity is the primary basic function of the environment in terms of supplying resources to human society, and reflects the proper level or total quantity of natural resources explored or consumed in a sustainable way. Local land resource and water resource are finite and sensitive to development, and so are usually considered by SEA, environmental planning and management. Energy resource is readily transferable and so is not incorporated in the local natural resources capacity. Therefore, the available water resource and suitable construction land resource are used herein to measure the natural resources capacity in CCE. Environmental assimilative capacity reflects the wastecontainment capacity of receiving waters and the atmosphere by the dispersal, transport, and treatment of waste. Water assimilative capacity and atmospheric assimilative capacity are separately accounted for when measuring environmental assimilative capacity in CCE. The ecosystem services capacity places particular emphasis on regulating, supporting, and cultural services, which are determined according to the ecosystem characteristics (e.g. category, and area). Alternative measurement indicators of ecosystem services include the value of biome services (Costanza et al., 1997), the Leaf Area Index (LAI) (Wang and Wang, 2004), the value of different land use types (Ran et al., 2006), and the area of ecological land (e.g. forest, wetland, or nature reserve). Herein Sum LAI and forest area have been adopted to measure the ecosystem services capacity in CCE. Society supporting capacity is an exogenous variable that affects CCE by changing its endogenous variables, the natural resources capacity, environmental assimilative capacity, and ecosystem services capacity. As the most active and manageable variable, the society supporting capacity is measured using Gross Domestic Product (GDP) per capita and proportion of total GDP invested in environmental protection. 2.4. Measuring CCE In summary, we select the following eight measurable indicators of CCE: available water resource, suitable construction land resource, water assimilative capacity, atmospheric assimilative capacity, Sum LAI, forest area, GDP per capita, and proportion of total GDP invested in environmental protection. The indicators of forest area, GDP per capita, and proportion of total GDP invested in environmental protection are directly derived from local statistical data. Sections 2.4.1e2.4.5 describe the methodologies by which the indicators are estimated. 2.4.1. Available water resource Available water resource is taken to be the maximum quantity of water that can be abstracted without an adverse spatial or temporal change occurring to the environment. Available surface water, available ground water, water intake, and wastewater reclamation are included in the measurement of available water resource from
WAR ¼ WAS þ WAG þ WI þ WWR WRC
(1)
where WAR is available water resource, WAS is available surface water, WAG is available ground water, WI is water transferred in, WWR is wastewater reclamation, and WRC is water counted both as available surface water and available ground water. 2.4.2. Suitable construction land resource Construction land resource is used for industrial production, infrastructure, recreational services, etc. Herein, suitable construction land resource is assigned as the measure of land supply for
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construction that should not impact adversely on a specific environment. This measure accounts for both suitable and less suitable land areas estimated through ecological assessment, whereby landform and land cover factors related to ecological suitability are mapped and overlaid according to different weights using GIS tools. Here, the suitability value for a land unit is estimated from
8 Cij ¼ 0 > <0 n P Ci ¼ Wj Cij Cij s 0; i ¼ 1; 2; .; m; j ¼ 1; 2; .; n > :
(2)
j¼1
where Ci is the suitability value of the i-th land unit, Cij is the suitability of the j-th factor in the i-th land unit, and Wj is the weight of the j-th factor. Land units are ranked according to whether construction is forbidden, limited, less suitable, or suitable. The combined area of less suitable construction land and suitable construction land is taken to be the suitable construction land resource. 2.4.3. Water assimilative capacity Water assimilative capacity refers to the ability of a body of water to carry waste without adverse effects on the environment or on the users of its resources. Water assimilative capacity is limited by the hydrodynamic and biological characteristics of the water body (Tett et al., 2007), water quality targets, and characteristics of pollutants and their discharge (Zhang and Liu, 1991). A water quality model is used to determine the water assimilative capacity, (Novotny and Krenkel, 1975), with a one-dimensional model generally applied to most water bodies, except for large, wide rivers where a two-dimensional model is often used. The details are set out in the China Technical Guide to Water Assimilative Capacity Determination (CAEP, 2003). In the present study, the water quality control section is set at a distance equal to 40% of the length of a given river reach, measured from the start of the reach. The water assimilative capacity is not single-valued but has a range of values that can alter according to the river discharge characteristics. A linear planning model is used to determine the maximum water assimilative capacity. 2.4.4. Atmospheric assimilative capacity Atmospheric assimilative capacity is defined as the maximum emission load that a region can assimilate without the air quality of the region deteriorating below a given threshold. Atmospheric assimilative capacity depends on a variety of environmental parameters, including meteorological conditions, terrain characteristics, and emission characteristics (see e.g. Goyal and Chalapati Rao, 2007). Various approaches are described in the literature for estimating the atmospheric assimilative capacity of a region. Goyal et al. (2006) propose two approaches, one based on a ventilation coefficient, the other through pollution potential. SEPA (2003) recommend an A-P value method and multi-source simulation model to estimate atmospheric assimilative capacity in China. However, the A-P value method is based on a box model using a ventilation coefficient, and is unable to provide a specific assimilative capacity as it does not incorporate terrain and emission characteristics. Alternatively, the multi-source simulation model (used herein) provides an estimate of atmospheric assimilative capacity based on air quality modeling which takes into consideration region-specific meteorological conditions, terrain characteristics, and emission loads from different sources. Following Goyal and Chalapati Rao (2007), the discharged emission load at which the maximum allowable concentration is reached under predefined critical conditions is taken to be the assimilative capacity of the region. Prediction of ground-level concentrations of pollutants is
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Table 1 Average LAI of biome/land cover type (m2/m2). Biome/Land cover
Farmland
Garden
Woodland
Grassland
Wetland
Water
Construction land
Other land
Average LAI
3.0
3.0
5.0
2.0
6.5
0
0.5
1.0
carried out using the US EPA approved ISCST-3 simulation model (EPA, 1995a, 1995b). It should be noted that the atmospheric assimilative capacity has a range of values, depending on the variation of emission characteristics with given meteorological and topographical conditions. The maximum value is determined using a linear planning model. 2.4.5. Sum LAI In the measurement framework of CCE, the ecosystem services focus on regulating, supporting, and cultural services. Therefore ecological capacity (Wackernagel and Rees, 1996) expressed by area of production land is not suitable for the measurement of ecosystem services capacity. Also emergy (Odum, 1987), value of biome services (Costanza et al., 1997), and value of different land use types (Ran et al., 2006) are not adopted because they would not provide a comparable estimate of the difference between supply and demand of ecological services. LAI is broadly defined as the amount of leaf area in a vegetation canopy per unit land area. Like net primary productivity, LAI is a key structural characteristic of vegetation and land cover because of the role of green leaves in a wide range of biological and physical processes (Scurlock et al., 2001), which dominates the function of ecosystem services in terms of land cover type and biome. Sum LAI, i.e. the sum of average LAI for all land cover types, is used to measure the difference between ecosystem services capacity (supply) and expectation (demand) in a region (Wang and Wang, 2004). Scurlock et al. (2001) compiled LAI data for 1008 samples obtained from more than 400 sites worldwide during the period 1932e2000, and summarized the averaged LAI for each of 15 main biomes/land cover types. Table 1 lists the averaged LAI for China obtained for different types of biome/land cover (see Costanza et al., 1997; Ran et al., 2006). The sum LAI is determined as follows: (1) The type of biome/land cover is identified by interpreting either remote sensing images or land use/land cover maps, counting the area ratio wi of the i-th biome to land cover type in a given region. (2) Sum LAI is then estimated from
LS ¼
n X
wi Li
(3)
i¼1
Here, LS is sum LAI in a given region, m2/m2, Li is average LAI of the i-th biome/land cover type determined from Table 1, m2/m2, and wi is the area ratio of the i-th biome to land cover type in the given region. (3) Set expectation of sum LAI. It is difficult to provide an exact expected value of sum LAI at the present day. However, by progressively increasing the sum LAI, the ecosystem services expand to meet the growing demand. Herein, the expectation of sum LAI in 2010, 2020, and 2050 is respectively set equal to 3, 4, and 5 m2/m2, the values based on the assumption that biome with high LAI will cover most of the land area in 2050. Assessment of the carrying state of ecosystems services is conducted by comparing the supply and expectation of sum LAI.
2.5. Assessment of CCE CCE assessment indicates to what degree CCE is transgressed by ES due to human disruption, and so provides very important scientific information to decision-makers. CCE assessment involves a set of comparable supply (CCE) and demand (ES) indexes, with the former being the threshold of the latter. The main technique to assess CCE involves comparing these paired indicators, making judgments as to whether the environment is capable of carrying or not, and then determining the degree of carrying or transgressing. 2.5.1. Indexes of assessing CCE Table 2 shows the three-layer index system used to assess CCE. In the objective layer, the CCE index is a comprehensive variable with four component indexes located in the middle layer. Each component index is derived from several basic indexes in the primary layer. The overall CCE index is denoted by c, with each component index denoted by ci, where i is 1, 2, 3 or 4.In the primary layer, each CCE basic index cij is paired with an ES basic index pij, where j is the respective sub index for the i-th component index. 2.5.2. Assessment of the basic indexes Once values of the paired basic indexes have been determined, assessment of the basic indexes is carried out using the carrying capacity surplus ratio dij defined as
Table 2 Assessment index system of CCE. Objective (c)
Middle (ci)
Primary CCE basic index (cij)
ES basic index (pij)
Unit
CCE
Natural resources capacity
Available water resource Suitable construction land resource Assimilative capacity of SO2 Assimilative capacity of NO2 Assimilative capacity of PM10 Assimilative capacity of COD Assimilative capacity of NH4eN Forest area Sum LAI GDP per capita Proportion of total GDP invested in environmental protection
Water consumption Construction land Emission of SO2 Emission of NO2 Emission of PM10 COD discharge NH4eN discharge Planned forest area Target Sum LAI Target GDP per capita Target proportion of total GDP invested in environmental protection
t/a km2 t/a t/a t/a t/a t/a km2 m2/m2 Yuan %
Environmental assimilative capacity
Ecosystem services capacity Society supporting capacity
R.Z. Liu, A.G.L. Borthwick / Journal of Environmental Management 92 (2011) 2047e2053
dij ¼
cij pij pij ¼ 1 cij cij
(4)
where cij is the CCE basic index, and pij is the ES basic index. The principle of assessment is the following. For dij > 0, the environment is capable of carrying stress due to human interference, and dij provides an estimate of the degree of surplus capacity. For dij < 0, the stress transgresses CCE, with dij representing the degree of transgression. For dij ¼ 0, when cij ¼ pij, the stress of human interference has reached the carrying capacity threshold, and no more stress should be placed on this index. 2.5.3. Assessment of the CCE index and its component indexes The CCE index may be regarded as a vector with four components, and the component index as a sub-vector with several basic indexes. A vector of surplus ratio of carrying capacity is proposed to assess the CCE index and its component indexes, the idea translated from vector assessment of regional carrying capacity (Yu and Mao, 2002). For component index assessment, we define the surplus ratio of the i-th component index as
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u X u 1 ni 2 pij Di ¼ 1 t r ; rij ¼ cij ni j ¼ 1 ij
(5)
where ni is the number of sub indexes of the i-th component index, and rij is the ratio of the ES basic index to the ECC basic index. Three states of carrying capacity in the component index are assessed for Di > 0, Di ¼ 0, and Di < 0, with the degree of carrying or transgressing represented by the value of Di. For assessment purposes, the surplus ratio of the CCE index, D, is obtained from
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u m u1 X D ¼ 1t ð1 Di Þ2 m
(6)
i¼1
where m is the number of sub components (equal to 4 in the present study). In keeping with the previous definitions, D represents the degree to which the environment carries stress. For D > 0, the environment is fully capable of carrying the stress induced by human interference, whereas for D < 0, the stress transgresses the CCE. 3. Results 3.1. Measurement of CCE in 2005 and 2010 Data on available surface water, available ground water, and double-counted water were gained from local detailed water resource reports (unpublished). Data on wastewater reclamation were obtained from published statistics for 2005 (Ningbo Bureau of Statistics, 2006), and from predictions for 2010 assuming 20% wastewater. It was also assumed that no water was transferred into or out of Ningbo. Table 3 lists the values of available water resources in Ningbo for 2005 and the predictions for 2010. The factors used to determine ecological suitability included drinking water source protection area, natural conservation area, volume of water body, land cover, fracture zone, mean gradient,
and traffic convenience (obtained using GIS). Suitability values were derived from overlays of the above factors according to Equation (2) using GIS tools. Land with a suitability value more than 4.6 was ranked as ‘suitable or less suitable’. The resulting total area of suitable construction land resource was 1728 km2 in Ningbo. One-dimensional numerical models recommended by CAEP (2003) were used to simulate the water quality of inland rivers and tidal river segments, and hence evaluate the water assimilative capacity for COD and NH4eN. The models considered a total of 36 river segments related to the Yaojiang River, Fenghuajiang River, and Yongjiang River. Model input included the start and end locations, flow volume, flow velocity, length, objective water quality, present water quality, and degradation coefficient for each section. Further input related to sewage discharge into the rivers included outlet position, discharge volume and velocity, and concentrations of COD and NH4eN. Maximum allowable discharge loads, i.e. assimilative capacity for COD and NH4eN, were summed to 13,440 t and 1211 t by running the models for all 36 segments of Ningbo. The ISCST-3 model was used to evaluate atmospheric assimilative capacity. Emission data were based on an emission declaration system and environment statistics, both provided by the local environmental protection bureau. Meteorological data at hourly intervals were collected by a local weather station. Receptor data included information from Ningbo Middle School, Ningbo College, Ningbo Fourth Middle School, and Longsai Hospital. Control conditions were set as default. Predictions have been made of the mean hourly ground-level concentrations of SO2, NO2, and PM10 pollutants at four receptors in 2005. Table 4 lists the predicted and measured mean annual concentrations, and API values derived from the mean hourly ground-level concentration data. As a result, the predicted and monitored numbers of days with API >100 were very close or equal to the criterion. This implies that emissions in 2005 may be equated to the allowable emissions, i.e. the atmospheric assimilative capacity for the given spatial distribution of emission sources. In this case, the atmospheric assimilative capacities of the SO2, NO2, and PM10 pollutants were 1.99 105, 1.62 105, and 4.76 104 t, respectively. The area of each biome/land cover type was derived using GIS tools from the vector map of land use derived from the annuallyupdated land records for 2005. The Sum LAI for 2005 was estimated to be 3.47 m2/m2 using Equation (3). For 2010, Sum LAI was predicted as 3.46 m2/m2, based on prediction of land use structure. From the local statistics, the estimated forest area was 4682.5 km2 in 2005; this value was unchanged in 2010, and is expected to remain the same for at least the near future. In 2005, the residential population of Ningbo was 6.136 million, with a GDP per capita of 38,733 RMB. Allowing for local development, the GDP per capita in 2010 is estimated to be 61400 RMB. The environmental protection investment rate was 2.96% GDP in 2005 according to local statistics. Using the local planning report (unpublished), the predicted value for 2010 is 3.02%.
3.2. Assessment of CCE in 2005 and 2010 In the calculation of CCE for 2005 and 2010, the value of ES for 2005 was derived from statistical data and that of ES for 2010 was Table 4 Predicted and monitored mean annual concentrations of atmospheric pollutants for Ningbo in 2005.
Table 3 Available water resources in Ningbo (unit: 108 t).
2005 2010
2051
Available surface water
Available ground water
Double-counted water
Wastewater reclamation
Available water resources
25.58 25.58
17.10 17.10
15.23 15.23
0.11 1.77
27.56 29.22
Predicted Monitored Criteria
SO2 (mg/m3)
NO2 (mg/m3)
PM10 (mg/m3)
Number of days API > 100 (d)
0.049 0.047 0.06
0.065 0.066 0.08
0.089 0.081 0.10
31 35 35
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predicted according to the Ningbo 11th National Economic and Social Development Plan. Supplementary Table 1 lists the resulting values of CCE and ES. The CCE basic indexes listed in Supplementary Table 2 were assessed using the carrying capacity surplus ratio model based on the values of the corresponding pairs of CCE and ES indexes. The results in Supplementary Table 2 indicate the following:
The following three prerequisites should be met. (1) Strict total quantity control of pollutants is required, with SO2 and COD reduced by 48% and 15% from the 2005 levels. (2) Improved management and technology should be used to reduce resource consumption and pollutant discharge. (3) Limits should be placed on population and economic goals. 4. Discussion
(1) The available water resources could carry water consumption, having a net surplus abundance that decreases from 27% in 2005 to 12% in 2010. (2) The land can support further construction, given the net surpluses of 24% in 2005 and 15% in 2010. (3) Water bodies were unable to carry the pollutant discharges of COD and NH4eN in 2005, as is evidenced by the respective shortages of 65% and 55% in assimilative capacity. And the shortages are predicted to decrease to 30% and 50% in 2010 respectively. Severely polluted rivers include the Fenghuajiang River and stagnant reaches on the Ningbo plain. (4) The atmospheric assimilative capacity was fully laden in 2005, when the number of days with API 100 decreased to the critical value of 330. It is predicted that the emission of SO2 will be reduced by 58% in order to achieve the required emission target in 2010. Even so, the emissions of NO2 and PM10 are estimated to exceed their assimilative capacities by 23% and 30% respectively in 2010. (5) The environment could supply the local inhabitants with sufficient ecosystem services. Forest area had a net surplus of 27% in both 2005 and 2010, and similarly the sum LAI was in surplus by 14% in 2005 and 13% in 2010. (6) GDP per capita and the resulting environmental protection investment were both insufficient to support improvement of the local environment in 2005. However, the GDP per capita rose considerably by 2010, helping reduce the shortage in environmental protection investment to 16% of GDP. The vector of surplus ratios of carrying capacity is next used to assess the CCE index and its component indexes. Fig. 2 indicates the carrying state for Ningbo, whose environmental stresses transgressed CCE by 2% in 2005, primarily because of pollutants overloading the local assimilative capacities. By 2010 however, it appears that the environment could carry the stresses from human development given a 3% abundance of CCE owing to societal support and the implementation of pollution mitigation measures.
Whole carrying state
0.5
Society supporting
0
Natural resources
-0.5
Ecosystem services
Assimilative capacity
2005
2010
Fig. 2. Assessment of ECC and its component indexes for Ningbo in 2005 and 2010.
A new definition of CCE has been proposed based on four components related to resource, environment, ecology, and society. These components are quantified in a way that distinguishes between ES and CCE, and clarifies the degree to which surplus or transgression occurs. The environment involves natural resources, assimilative capacity, and ecosystem services, all of which can be changed by human society. In practice, SEA and environmental planning deal with all four aspects of the environment. Thus the present method provides a systemic, straightforward basis for the measurement and assessment of CCE and its four components. However, the four key indictors selected herein to describe CCE are not comprehensive and further indicators such as energy supply and soil assimilative capacity may be added in a future study. The case study of Ningbo demonstrates the model is useful in practice, though further work is needed to improve the representation of ecosystem services (given the difficulty encountered in assessing the correct match of demand to supply). A carrying capacity surplus ratio model has been used to assess basic indexes, and a vector of surplus ratio of carrying capacity model established for integrated indexes. The former model was designed to compare directly the CCE and ES basic indexes. This provides a convenient and accurate judgment as to whether transgression occurs, and a measure of the degree to which the threshold of each basic index is either transgressed or exceeded. The latter model calculates the Euclidean vector of surplus ratios instead of linear plus. The integrated assessment inherently incorporates the nonlinear relationships between a vector and its sub-vectors, avoiding inaccuracy from the conventional linear plus method and its subjective weights. Both models have also been applied to the case study for Ningbo, demonstrating their capability for quantitative assessment of CCE and its basic indexes in practice. However, it should be noted that considerable effort was required to prepare the database, carry out model predictions, and determine the basic indexes, before obtaining the CCE index for Ningbo. In practice, it may be sensible to carry out an auxiliary assessment in relatively straightforward cases where a quick assessment is required at low cost. Qualitative assessment of CCE should be performed by comparing indicators of environmental quality and ecological quality, which are regularly monitored (e.g. mean annual concentration of pollutants or vegetation cover ratio), according to prescribed criteria, instead of comparing ES basic indexes with CCE basic indexes. 5. Conclusions A comprehensive measurement system for CCE has been proposed. It is based on a new definition of CCE and comprises measurable models for natural resources supply, environmental assimilative capacity, ecosystem services supply, and society supporting capacity. The measurement system is useful and applicable because it covers the full dimensions of CCE, and includes models for suitable construction land resource and ecosystem services in addition to other more established models. The index system for assessment of CCE has been designed to correspond to the measurement system. A carrying capacity surplus ratio model and a vector of surplus ratio of carrying capacity model are respectively
R.Z. Liu, A.G.L. Borthwick / Journal of Environmental Management 92 (2011) 2047e2053
proposed to assess the basic index states and the integrated index state for CCE. The assessment models rely on a direct comparison of CCE and ES for each basic index, use a Euclidean vector for integration instead of linear plus, and thus produce convenient, accurate, and quantitative assessment results. The case study of Ningbo has demonstrated the assessment of CCE in practice. In 2005, Ningbo’s environmental stress transgressed CCE by 2%. Local water bodies were unable to carry pollutant discharges of COD and NH4eN, the shortfalls being 65% and 55% of assimilative capacity. The GDP per capita and environmental protection investment in GDP also undershot their respective thresholds by 16% and 18%. In 2010, however, the situation has changed, with the environment apparently able to carry further stress from human development (given a 3% abundance of CCE) by enhanced societal support and pollution mitigation. Acknowledgments This research was supported by the National Natural Science Foundation of China under Grant No. 40801229 and the National High Technology Research and Development Program of China under Grant No. 2007AA06A404. The authors are grateful to Prof. Hao Jiming and Prof. Wang Chengwen of Tsinghua University, and Ningbo Environmental Protection Bureau for their assistance regarding the case study of Ningbo. Appendix. Supplementary information Supplementary data related to this article can be found online at doi:10.1016/j.jenvman.2011.03.033. References Arrow, K., Bolin, B., Costanza, R., Dasgupta, P., Folke, C., Holling, C.S., Jansson, B.O., Levin, S., Mäler, K.G., Perrings, C., Pimentel, D., 1995. Economic growth, carrying capacity, and the environment. Science 268, 520e521. Baldwin, J.H., 1985. Environmental Planning and Management. Westview Press, Boulder. Bartels, G.B., Norton, B.E., Perier, G.K., 1993. An examination of the carrying capacity concept. In: Behnke Jr., R.H., Scoones, I., Kerven, C. (Eds.), Range Ecology at Disequilibrium. Overseas Development Institute, London, pp. 89e103. Chinese Academy for Environmental Planning (CAEP), 2003. China Technical Guide of Water Assimilative Capacity Determination (in Chinese). Clarke, A.L., 2002. Assessing the carrying capacity of the Florida Keys. Population and Environment 23, 405e418. Costanza, R., d’Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’Nell, R.V., Raskin, R.G., Stutton, P., van den Belt, M., 1997. The value of the world’s ecosystem services and natural capital. Nature 387, 253e260. Daily, G.C., Ehrlich, P.R., 1996. Socioeconomic equity, sustainability, and Earth’s carrying capacity. Ecological Applications 6, 991e1001. EPA2454 /B2952003a, 1995a. User’s Guide for the Industria1 Source Complex (ISC3) Dispersion Models. In: User Introductions, vol. I. US EPA, Washington. EPA2454 /B2952003b, 1995b. User’s Guide for the Industria1 Source Complex (ISC3) Dispersion Models. In: Description of Model Algorithms, vol. II. US EPA, Washington. Godschalk, D.R., Parker, F.H., 1975. Carrying capacity: a key to environmental planning. Journal of Soil and Water Conservation 30, 160e165.
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