Evaluation of sustainability for intensive farmland ecosystem based on emergy ecological footprint.

Ecological footprint (EF) and emergy analysis (EA) are two important methods in evaluating regional or system sustainability. The EF is a quantitative tool that uses material and energy flows to estimate the biophysical 'load' imposed by human populations or industrial processes on ecosystems around the world. It is a useful indicator of sustainable development that showed the size of the biologically productive area necessary for resourcing the current consumption patterns when using common technologies. Emergy Analysis (EA) is an ecological accounting method used to comprehensively account all the inputs involving energies, natural resources consumption, and financial payments for humans by using similar units (sej). EA has been proven as an effective tool to evaluate the resource flows, support both the natural system and the economic system, and also provide a useful method for measuring the sustainability of systems. Emergy Ecological Footprint (EEF), which is a combination of these two methods, is considered to be able to measure resource consumption and environmental impact more comprehensively. Using the EEF method in this paper, we evaluated the winter wheat-summer maize rotation system, which is a typical cropping system in Huantai County located in Northern China, to try to reveal the control effect of agricultural non-point source pollution in the past decade. The results showed that compared to 1996, the total emergy input decreased by 3.15% in 2012. Phosphorus fertilizer, electricity energy for water pollution treatment, and nitrogen fertilizer are the top three contributors. The emergy of phosphorus fertilizer increased while the emergy of the other two decreased. But the emergy output capacity (EOC) increased by 6.23% due to the improvement in system efficiency. The EEF ranged from 40.94 to 39.59 hm2, which decreased by 3.30%. Meanwhile, the Resource Footprint (RF) increased 2.29 hm2, whereas the Environment Footprint (EnF) decreased 3.63 hm2. The emergy carrying capacity (ECC) had little change, ranging from 2.49 to 2.51 hm2a. The value of the EEF is 16.42 times the value of the ECC in 1996 and 15.76 times the value of the ECC in 2012, and ecological deficit reached up to 38.45 hm2 and 37.08 hm2, respectively, and declined when reduced by 3.56%. From the perspective of system sustainability, the results showed that the Resource Load Index (RLI) decreased by 4.02%, Environmental Load Index (ELI) reduced by 27.90%, System Externality (SE) reduced by 8.06%, but the Sustainability Index (SI) increased by 9.64%, suggesting that the winter wheat-summer maize rotation system in Huantai County consumed less energy, while the environmental impact caused by external input was weakened, and the sustainability level was improved. These results indicate that the non-point source pollution in Huantai County has been controlled significantly in the past decade. Overall, compared to 1996, the ecological deficit of the winter wheat-summer maize system decreased in 2012 while the sustainability and efficiency of the local farmland ecosystem increased. However, the amount of resources consumption and the environmental pressure of grain production still keep high levels, which mean the control of non-point source pollution in Huantai County needs to keep going ahead in the future. EEF provided us a new way to measure ecological sustainability, and it compensated several drawbacks of EF. Nevertheless, the EEF demonstrated the ecological carrying capacity entirely from a new perspective, and the meaning of ECC has been changed. In EEF, the ECC could only be decided by local natural conditions and failed to reflect the contribution of scientific and technological progress or productivity improvement. In order to make up for it, we designed the indicators of RLI, ELI, and SI, which integrated ecological footprint, productivity, and ecological carrying capacity for a better interpretation of the system sustainability. Agricultural production highly depends on natural conditions, so EEF might be more suitable for research in the field of agriculture systems than EF. [ABSTRACT FROM AUTHOR]