Abstract
With the development of agricultural modernization, the carbon emissions caused by the agricultural sector have attracted academic and practitioners’ circles’ attention. This research selected the typical agricultural development province in China, Fujian, as the research object. Based on the carbon emission sources of five main aspects in agricultural production, this paper applied the latest carbon emission coefficients released by Intergovernmental Panel on Climate Change of the UN (IPCC) and World Resources Institute (WRI), then used the ordered weighted aggregation (OWA) operator to remeasure agricultural carbon emissions in Fujian from 2008–2017. The results showed that the amount of agricultural carbon emissions in Fujian was 5541.95 × 103 tonnes by 2017, which means the average amount of agricultural carbon emissions in 2017 was 615.78 × 103 tonnes, with a decrease of 13.13% compared with that in 2008. In terms of spatial distribution, agricultural carbon emissions in the eastern coastal areas were less than those in the inland regions. Among them, the highest agricultural carbon emissions were in Zhangzhou, Nanping, and Sanming, while the lowest were in Xiamen, Putian, and Ningde. In addition, this paper selected six influencing variables, the research and development intensity, the proportion of agricultural labor force, the added value of agriculture, the agricultural industrial structure, the per capita disposable income of rural residents, and per capita arable land area, to clarify further the impacts on agricultural carbon emissions. Finally, geographically- and temporally-weighted regression (GTWR) was used to measure the direction and degree of the influences of factors on agricultural carbon emission. The conclusion showed that the regression coefficients of each selected factor in cities were positive or negative, which indicated that the impacts on agricultural carbon emission had the characteristics of geospatial nonstationarity.
Highlights
Since the 21st Century, global warming, which is mainly caused by the increase of the carbon dioxide concentration in the atmosphere, has attracted widespread attention
In order to consider fully the dynamic evaluation of the panel data, the weights of each year based on ordered weighted averaging (OWA) are listed in the last row of Table 2, while the average agricultural carbon emissions of each region calculated based on OWA are listed in the last column
By comparing the coefficients estimated by geographically-weighted regression model (GWR) and geographically- and temporally-weighted regression (GTWR), it was found that the coefficients varied greatly, which indicates that the direction and degree of the impacts of influencing factors on agricultural carbon emissions were different in both the time and space dimensions, which shows significant spatial and temporal non-stationarity characteristics
Summary
Since the 21st Century, global warming, which is mainly caused by the increase of the carbon dioxide concentration in the atmosphere, has attracted widespread attention. In order to promote the development of agricultural production, this can only be done by adding the inputs of chemical fertilizers, pesticides, and agricultural film for Fujian to increase the outputs of grain and other cash crops These measures have resulted in a large amount of carbon emissions, causing serious environmental pollution. In order to effectively promote the reduction of carbon emissions in the agricultural sector and complete the construction of the ecological civilization pilot zone, it is of great significance to carry out research on Fujian’s agricultural carbon emissions. By adopting the GTWR model, this paper analyzes the spatial-temporal heterogeneity of the impact of factors on agricultural carbon emissions, aiming to establish an effective agricultural carbon emission reduction mechanism, and aiding local sustainable development decision-making
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