Agricultural CO2 Emissions Research Articles

Shocks in agricultural productivity and CO2 emissions: new environmental challenges for China in the green economy

The primary motive behind this research is to see the role of China’s large agriculture sector in promoting or demoting CO2 emissions. Therefore, we applied linear and non-linear ARDL models by collecting data over the period 1971–2019 for China. The results of the linear model suggest that livestock production can help to reduce CO2 emissions both in the short and long run. In the non-linear model, the short-run estimates of livestock production are insignificant, however, in the long run, the positive shock in the livestock production helps to reduce the CO2 emissions and the negative shock is insignificant. On the other side, an increase in crop production deteriorates the environmental quality in the short run in both linear and non-linear models. In long run, the estimate of crop production in the linear model is insignificant and in the non-linear model, the estimated coefficients of both positive and negative shocks in crop production are negative implying that a positive shock reduces the CO2 emissions while the negative shock increases the CO2 emissions.

Soil carbon sequestration potential of planting hedgerows in agricultural landscapes

Realising the carbon (C) sequestration capacity of agricultural soils is needed to reach Paris Climate Agreement goals; thus, quantifying hedgerow planting potential to offset anthropogenic CO2 emissions is crucial for accurate climate mitigation modelling. Although being a widespread habitat in England and throughout Europe, the potential of hedgerows to contribute to net-zero targets is unclear. This is the first study to quantify the soil organic carbon (SOC) sequestration rate associated with planting hedgerows. We derived SOC stocks beneath hedgerows based on two estimation methods to assess differences from adjacent intensively managed grassland fields and how these may be affected by sampling depth and hedgerow age, as well as the SOC estimation method used. Twenty-six hedgerows on five dairy farms in Cumbria, England, were classified based on the time since their planting. We measured SOC stocks in 10 cm depth intervals in the top 50 cm of soil beneath hedgerows and in adjacent grassland fields. SOC beneath hedgerows was on average 31.3% higher than in the fields, 3.3% for 2–4 year old hedgerows, 14.4% for 10 year old, 45.2% for 37 year old, and 57.2% for older ones. We show that SOC sequestration rate beneath 37 year old hedgerows was 1.48 Mg C ha−1 yr−1 in the top 50 cm of soil. If England reaches its goal of a 40% increase in hedgerow length, 6.3 Tg CO2 will be stored in the soil over 40 years, annually offsetting 4.7%–6.4% of present-day agricultural CO2 emissions. However, the current rate of planting funded by agri-environment schemes, which today reaches only 0.02% of emissions, is too slow. Private-sector payments for ecosystem services initiatives (e.g., ‘Milk Plan’) show much higher rates of planting and are needed alongside agri-environment schemes to ensure hedgerow planting contributes to net-zero targets.

Driving factors and decoupling trend analysis between agricultural CO2 emissions and economic development in China based on LMDI and Tapio decoupling.

Based on mathematical models, in-depth analysis about the interrelationship between agricultural CO2 emission and economic development has increasingly become a hotly debated topic. By applying two mathematical models including logarithmic mean divisia index (LMDI) and Tapio decoupling, this work aims to study the driving factor and decoupling trend for Chinese agricultural CO2 emission from 1996 to 2020. Firstly, the intergovernmental panel on climate change (IPCC) method is selected to estimate the agricultural CO2 emission from 1996 to 2020, and the LMDI model is adopted to decompose the driving factors of agricultural CO2 emission into four agricultural factors including economic development, carbon emission intensity, structure, and labor effect. Then, the Tapio decoupling model is applied to analyze the decoupling state and development trend between the development of agricultural economy and CO2 emission. Finally, this paper puts forward some policies to formulate a feasible agricultural CO2 emission reduction strategy. The main research conclusions are summarized as follows: 1) During the period from 1996 to 2020, China's agricultural CO2 emission showed two stages, a rapid growth stage (1996-2015) and a rapid decline stage (2016-2020). 2) Agricultural economic development is the first driving factor for the increase of agricultural CO2 emission, while agricultural labor factor and agricultural production efficiency factor play two key inhibitory roles. 3) From 1996 to 2020, on the whole, China's agricultural sector CO2 emission and economic development showed a weak decoupling (WD) state. The decoupling states corresponding to each time period are strong negative decoupling (SND) (1996-2000), expansive negative decoupling (END) (2001-2005), WD (2006-2015) and strong decoupling (SD) (2016-2020), respectively.

Using an asymmetrical technique to assess the impacts of CO2 emissions on agricultural fruits in Pakistan.

Human activities such as deforestation and cultivation contribute to the accumulation of carbon dioxide in the environment. Methane is emitted by energy exploration, coal mining, natural gas spills, waste, and waste dumps. Methane generated by such greenhouse gases has significantly contributed to the climate change and global warming. However, the most significant contributor to climate change and global warming is the use of fossil fuels. These fuels contribute to ozone depletion and global warming by emitting greenhouse gases into the atmosphere. The current study key objective was to determine the CO2 emission effect to key fruit production in Pakistan by taking time series annual data varies from 1970 to 2019. A non-linear autoregressive distributed lag model (NARDL) was employed to check the variables linkages. The consequences of short- and long-run estimates expose that the positive and adverse shocks of citrus fruit create expressively to upsurge the CO2 emission. Similarly, the positive and negative shocks of mango fruit expose an adverse interaction to CO2 emission. The positive shock of apple fruit has constructive but negative shock expose and adverse linkage to CO2 emission. Further, banana fruit also exposes a negative but constructive via positive shock linkage to CO2 emission. Moving towards the apricot fruit production that exposed a constructive linkage via positive and negative shocks to CO2 emission. The almond fruit productivity via positive and negative shocks exposed an adverse relation to carbon dioxide emission. Grape fruit via positive shock shows a construct, but negative shock exposed an adverse association to carbon emission in Pakistan. Finally the guava fruit production exposed a construct linkage to CO2 emission via positive and negative shocks. Since agricultural activities and CO2 emissions are essential to resolving the pollution problem, a series of practicable steps must be taken by the Pakistani authorities to tackle this issue.

Assessment of major food crops production-based environmental efficiency in China, India, and Pakistan.

Global warming and food security have led to increasing concern about agricultural crop production efficiency, especially wheat and rice farming. The purpose of the current study is to measure wheat and rice production efficiency scores with environmental quality in China, India, and Pakistan by using a data envelopment analysis (DEA) model. The DEA results show that China and India are more efficient in wheat and rice production but it is not efficient in the environment in the study period. The results also show that Pakistan has also relatively small wheat and rice efficiency compared with China and India and increased the efficiency with the passage of time. The practical outcomes also show that Pakistan has the most efficient and effective states from the periods 2008 to 2019 in terms of wheat and rice efficiency and also a small increase in carbon emission. Based on the findings, policymakers should pay attention to the role of green technology in reducing agricultural CO2 emissions.

Decoupling analysis and scenario prediction of agricultural CO2 emissions: An empirical analysis of 30 provinces in China

This study explores the decoupling status and the future trend of CO2 emissions from agricultural sector. First, this study uses the Log-Mean Divisia Index (LMDI) model to identify the driving forces that affecting the agricultural CO2 emissions from 2008 to 2017. Over the study period, the per capita cultivated area (PCA) and rural population (RP) were two main factors for increasing and decreasing agricultural CO2 emissions, respectively. Then the Tapio model was conducted to reflect the relationship between the agricultural CO2 emissions and agricultural output. Six decoupling statuses exited across provinces through the whole period. Strong decoupling status was observed in seven provinces, such as Hebei, while nine provinces experienced weak decoupling, such as Henan. Besides, coupling status still existed in fourteen provinces. Based on the provincial decoupling results, we establish three scenarios namely business-as-usual (BAU), median case of decoupling (MCD) and best case of decoupling (BCD) scenarios to estimate agricultural CO2 emissions in 2030. MCD scenario assumes that coupling status will not exit in provinces and all provinces could achieve strong decoupling in BCD scenario. Results reveal that China's agricultural CO2 emissions in 2030 will be 366.7 Mt, 224.9 Mt and 175.3 Mt under three scenarios, respectively. The agricultural CO2 emissions in MCD and BCD scenarios are 38.7% and 52.2% lower than those in BAU scenario in 2030, respectively. Inner Mongolia, Jilin, Jiangsu, Guangxi and Xinjiang should be given priority to promoting decoupling status under the MCD scenario due to their huge emission reduction potential.

The decoupling study of agricultural energy-driven CO2 emissions from agricultural sector development

The decoupling study of agricultural energy-driven CO2 emissions from agricultural sector development

Nitrogen availability determines the long-term impact of land use change on soil carbon stocks in grasslands of southern Ghana

Abstract. Enhancing the capacity of agricultural soils to resist soil degradation and to mitigate climate change requires long-term assessments of land use systems. Such long-term evaluations, particularly regarding low-input livestock systems, are limited. In the absence of suitable long-term experiments, this study assessed the outcome of C inputs and outputs across an array of plant functional groups in arable and permanent systems of a tropical savannah after more than 50 years of consistent land use. Soil samples were taken (0–30 cm depth) from arable crop fields, grazed–seeded grassland, cut–use permanent crops and native grassland. Soil organic carbon (SOC) stocks ranged from 17 to 64 Mg SOC ha−1 (mean ± sd = 32.9 ± 10.2 Mg ha−1). SOC stocks were lower for grazed–seeded grassland relative to cut–use grass, legume trees and shrubs. Accordingly, while the conversion of the native grassland to grazed pastures caused an estimated loss of 44 % of SOC over the period, the conversion to woody legumes resulted in slight (5 %), incremental gains. Within sown systems, nitrogen (N) availability seemed to be the most critical factor in determining the fate of the SOC stocks, with the soil N concentration and SOC being highly correlated (r – 0.86; p < 0.001). In total N, P and K were significant predictors of SOC density in the soils. Moreover, secondary plant metabolites in legumes, namely tannins, were identified as having an impact on SOC. The results from this study provide the theoretical basis for testing the hypothesis that improved soil fertility management and the use of tannin-rich plants have the potential to promote long-term SOC storage in the savannah ecological region. Our study also shows the potential of legume tree/shrub forage species as an environmentally sustainable land use option to mitigate agricultural CO2 emissions from low-input livestock systems in the grasslands of southern Ghana.

Energy-related CO2 emissions and structural emissions’ reduction in China’s agriculture: An input–output perspective

The greenhouse effect caused by excessive carbon emissions seriously threatens the sustainability of the global economy. Although the secondary and tertiary industries are the principal contributors to CO2 emissions’ growth, the continuous and stable development of agriculture also intensifies carbon emissions to a certain extent. Based on this, this paper uses the input–output method, an energy consumption model, and structural decomposition analysis to study energy-related CO2 emissions and structural emissions’ reduction in China’s agriculture from 2007 to 2017. The research results show that (1) In 2007–2017, the input structure effect and the energy intensity effect inhibited the growth of energy-related CO2 emissions in China’s agriculture, with the reduction effect of energy intensity effect being the more prominent, whereas the final demand effect and the energy structure effect contributed to promoting China’s agricultural energy-related CO2 emissions’ growth, with the final demand effect being the greater promoting factor. (2) The energy structure effect failed to reduce energy-related CO2 emissions in China’s agriculture because the optimization of consumption structure is still not obvious on China’s agricultural supply-side. The share of energy consumption from high-carbon fuels such as raw coal, coke, and other washed coal has increased, rather than decreased, and the optimization of low-carbon energy sources such as natural gas is still slow, thus limiting the emissions’ reduction effect in the energy structure. (3) The reason why the final demand effect has promoted the growth of energy-related CO2 emissions in China’s agriculture is the expanding demand for agriculture in the entire industrial system. Specific to each industry, the secondary industry has played a major role in the final demand effect, accounting for more than 50% of the final demand effect, followed by the primary and the tertiary industries. Finally, this paper provides a theoretical and practical basis for accurately and efficiently implementing emissions’ reduction from the perspectives of the industrial system on the demand-side and the energy system on the supply-side and also in China’s agriculture.

Agricultural production and CO2 emissions from two sources in the ECOWAS region: New insights from quantile regression and decomposition analysis

Agriculture being the dominant economic activity of the West African economies is responsible for the most greenhouse gasses emitted in the region. Are there heterogeneous determinants of environmental degradation across low, intermediate, and high CO2 emitters in West Africa? Considering the significance of agriculture, industrial activities, renewable energy consumption and economic growth in West-Africa, this paper investigates the conditional determinants of environmental degradation from two sources (per-capita CO2 emission and CO2 emission from liquid sources) using panel data from 15 ECOWAS countries for the period 1990–2015. The study adopts a panel quantile regression technique with non-additive fixed effects as well as quintile decomposition techniques to explore if the relationship between agricultural and economic factors differs across low, intermediate, and high CO2 emitters and the extent of CO2 emission gap between Low Income Group (LIG) and Lower-Middle Income Groups (LmIG). Results from the mean estimators show that while agricultural production impedes CO2 emissions from liquid sources, it however increases total emissions implying a shift from mechanized farming to more traditional farming methods and the burning and use of biomass from agricultural produce as an energy source. Estimates of the conditional determinants of environmental degradation vary along the quantiles signifying heterogeneity of the determinants of environmental degradation across, low, intermediate, and high CO2 emitters. Additionally, results emanating from the quantile decomposition procedure show that lower-income West African economies have superseded their lower-middle income counterparts at higher quantiles of CO2 emissions.

The Nexus of Greenhouse Gas Emissions and Agriculture Sector: Case of Turkey and China

Greenhouse gas emissions constitute the basis of global warming. One of the sectors contributing to the greenhouse gas emissions is the agriculture sector which accounts for 24% of the global greenhouse gas emissions. In this study, the effect of cattle husbandry, small ruminant husbandry, poultry husbandry, paddy production, which are the main causes of emissions in the agriculture sector, on agricultural CO2 release was investigated. The research covers the years 1991-2017 of Turkey and China. In the study, time-series analyses such as Augmented Dickey-Fuller Breakpoint Unit Root Test, Johansen Cointegration Test, Ordinary Least Square Regression, Full Modified Ordinary Least Square, Canonical Cointegrating Regression and Impulse-Response Analysis were used. According to the results of the analysis, the effects of cattle husbandry, small ruminant husbandry, and paddy production activities on agricultural CO2 emissions were statistically significant in Turkey. We determined that the most effective variable on agricultural CO2 emissions was cattle husbandry both in the long- and short-term. On the other hand, poultry farming had no statistically significant effect on agricultural CO2 emissions. According to the results of the analysis for China, all variables were statistically significant. As a result, it is important to adopt methods that will not cause environmental damage or will have minimal impact in determination processes of effective parameters on agricultural CO2. The government should determine the boundaries of agricultural production processes through legal arrangements and the relevant ministries should implement them seriously. To take these measures and implement them are seen as a necessity for a sustainable world and a sustainable agricultural sector.

Achieving Food Security in a Climate Change Environment: Considerations for Environmental Kuznets Curve Use in the South African Agricultural Sector

This study relates agricultural income and agricultural carbon dioxide (CO2) emissions in the context of environmental Kuznets curves for South Africa. We posit likely relationships between UN Sustainable Development Goals (SDG) 1, 2 and 13, relating food production to climate change action. CO2 emissions, income, coal energy consumption and electricity energy consumption time series data from 1990 to 2012 within the South African agricultural sector were used. The autoregressive distributive lag bounds-test and the error correction model were used to analyse the data. The results show long-run relationships. However, agricultural income was only significant in the linear and squared models. Changes in agricultural CO2 emissions from the short run towards the long run are estimated at 71.9%, 124.7% and 125.3% every year by the linear, squared and cubic models, respectively. Exponentially increasing agricultural income did not result in a decrease in agricultural CO2 emissions, which is at odds with the Kuznets hypothesis. The study concludes that it will be difficult for South Africa to simultaneously achieve SDGs 1, 2 and 13, especially given that agriculture is reliant upon livestock production, the largest CO2 emitter in the sector. The sector needs to shift to renewable energy consumption with fewer CO2 emissions.

Earthworms regulate ability of biochar to mitigate CO2 and N2O emissions from a tropical soil

Soils account for >80% and 20% of the total agricultural N2O and CO2 emissions respectively. Soil management activities that target improved soil health, such as enhancing earthworm activity, may also stimulate further emissions of CO2 and N2O. One recommended strategy for mitigating these soil emissions is biochar amendment. However greater clarity on the interaction between earthworm activity and biochar, and subsequent impact on CO2 and N2O are needed to evaluate the environmental impacts of management practice. We measured N2O and CO2 emissions from a kaolinitic Acrisol in the presence or absence of earthworms, with and without application of two different biochars in a microcosm study. The two biochars were derived from indigenous trees; Zanthoxylum gilletii and Croton megalocarpus, and were tested at three application rates of 5 Mg ha−1, 10 Mg ha−1 and 25 Mg ha−1. Emissions of CO2 and N2O increased by 26% and 72% respectively in the presence of earthworms. In microcosms with biochar and earthworms however, emissions depended on type of biochar and rate of application. With C. megalocarpus, CO2 emission increased with increasing rates of biochar application with 25 Mg ha−1 resulting in higher CO2 fluxes compared to no-biochar control (p = 0.002), while no change was observed with Z. gilletii at the same rate. Nitrous oxide emissions were suppressed at 25 Mg ha−1 for both C. megalocarpus (p = 0.009) and Z. gilletii (p = 0.011). Reduction in N2O flux was however not consistent across biochar types. No change in N2O was observed with 5 Mg ha−1 and 10 Mg ha−1of C. megalocarpus. Biochar from Z. gilletii at 5 Mg ha−1 however led to increase in N2O emissions (p < 0.001). Our findings suggest that earthworms may moderate the effect of biochar, with suppression of N2O emissions occurring at only high biochar application rates, which may occur at the cost of increasing CO2 emissions. These findings contrast with biochar suppressing effect on N2O emissions even at moderate biochar rates of (10 Mg ha−1) when in absence of earthworms, an outcome typical of many laboratory experiments. These findings highlight new interactions among application rate, source of biochar (and hence properties) and earthworms.

Effectiveness of enhanced mineral weathering as a carbon sequestration tool and alternative to agricultural lime: An incubation experiment

Applying finely ground silicate minerals to soils could mitigate CO2 emissions by enhancing the rate of carbon sequestration via silicate weathering. Using these minerals instead of agricultural lime to increase soil pH would also eliminate the dissolution of lime as a major source of agricultural CO2 emissions. However, dissolution rates of silicate minerals in the soil environment are uncertain and impacts of their application on the decomposition of soil organic matter have yet to be determined. A 3-month soil incubation was performed to investigate the effects of olivine, a highly weatherable silicate mineral, at two application rates (OLIVlow, OLIVhigh) on soil CO2 flux, available Mg and Al, and pH in comparison to control and lime-amended soils. There was no difference in cumulative net CO2 flux between the olivine-amended soils and the control though total flux from the limed soils was 221% higher than the control. Heterotrophic respiration was also greatest in the lime-amended soils. The weathering rate of OLIVlow (26.7%) was higher than of OLIVhigh (7.1%), but both treatments increased soil pH to a level sufficient to overcome aluminum toxicity. Our results suggest that olivine amendments are an effective tool for carbon sequestration and a suitable replacement for lime.

Does agricultural ecosystem cause environmental pollution in Pakistan? Promise and menace.

The increasing trend of atmospheric carbon dioxide (CO2) is the main cause of harmful anthropogenic greenhouse gas emissions, which may result in environmental pollution, global warming, and climate change. These issues are expected to adversely affect the agricultural ecosystem and well-being of the society. In order to minimize food insecurity and prevent hunger, a timely adaptation is desirable to reduce potential losses and to seek alternatives for promoting a global knowledge system for agricultural sustainability. This paper examines the causal relationship between agricultural ecosystem and CO2 emissions as an environmental pollution indicator in Pakistan from the period 1972 to 2014 by employing Johansen cointegration, autoregressive distributed lag (ARDL) model, and Granger causality approach. The Johansen cointegration results show that there is a significant long-run relationship between the agricultural ecosystem and the CO2 emissions. The long-run relationship shows that a 1% increase in biomass burned crop residues, emissions of CO2 equivalent of nitrous oxide (N2O) from synthetic fertilizers, stock of livestock, agricultural machinery, cereal production, and other crop productions will increase CO2 emissions by 1.29, 0.05, 0.45, 0.05, 0.03, and 0.65%, respectively. Further, our finding detects that there is a bidirectional causality of CO2 emissions with rice area paddy harvested, cereal production, and other crop productions. The impulse response function analysis displays that biomass-burned crop residues, stock of livestock, agriculture machinery, cereal production, and other crop productions are significantly contributing to CO2 emissions in Pakistan.

Decoupling CO2 emissions from economic growth in agricultural sector across 30 Chinese provinces from 1997 to 2014

This paper investigates the decoupling of carbon dioxide (CO2) emissions from agricultural economic growth in 30 Chinese provinces from 1997 to 2014. First, CO2 emissions from agricultural production activities, farming, and livestock husbandry are computed. Then, this paper explores the spatial and temporal heterogeneity of CO2 emissions and their intensity in China’s agricultural sector. Finally, this paper compares decoupling of China’s agricultural CO2 emissions from agricultural output value across different regions and years. The results indicate that fertilizer, in-season rice cultivation, and cattle generated the most CO2 emissions in the categories of agricultural production activities, farming, and livestock husbandry, respectively. The results also show that East China covered more periods of the strong decoupling of CO2 emissions from agricultural output value between 1997 and 2014. To decrease CO2 emissions, this paper suggests imposing a higher value-added tax on fertilizer producers, while waiving value-added tax for organic fertilizer and substituting animal manure for conventional fertilizers where possible.

Technology gap and CO2 emission reduction potential by technical efficiency measures: A meta-frontier modeling for the Chinese agricultural sector

The purpose of this paper is to explore CO2 emission efficiency in china’s agricultural sector during the period 2001–2012. We also analyze the CO2 emission reduction potential as well as its two main contributors (i.e. technology gap inefficiency and managerial failure). The meta-frontier framework is adopted to reflect technology heterogeneities in China’s agricultural sector among the eastern, central and western regions. Based on the DEA (data envelopment analysis) method, the models are estimated by means of linear programming. Empirical results indicate that CO2 emission efficiency of the agricultural sector in western China is the lowest compared with eastern and central China; stemming from the fact that most provinces in western China generally fall behind in terms of technology. The total potential agricultural CO2 emissions reduction is estimated at 1161.33 million tons, which can be attributed to managerial failure in the case of eastern and central China. For western China, it can be attributed to both technological gap inefficiency and managerial failure.

Economic metrics to estimate current and future resource use, with a focus on water withdrawals

Demand for, and use of, water, food and energy resources is already straining mostly non-renewable supplies (e.g. freshwater resources). Population growth, climate change and shifting socio-economic standards mean that these resources will be stretched to critical levels. This paper uses historical data of GDP and GDP-per-capita to identify correlations with 19 water, food and energy metrics (e.g. water withdrawals, total food production and electricity generation and consumption), and subsequently attempts to estimate plausible resource use and demand for a suite of seven GDP growth scenarios, focusing on water resources. It is shown that GDP-per-capita is weakly correlated with all metrics, however total GDP shows stronger correlation. Best-fit regressions and the statistical distributions of historical data were used to replicate the historical data and validate derived correlations. Following this, the GDP scenarios were used to estimate plausible global total water withdrawals, food production and electricity generation and consumption to 2100. If recent GDP growth is maintained, then the ‘safe planetary boundary’ for total freshwater withdrawal of 4000 km3 yr−1 is surpassed in c. 29% of simulations (out of 8700 simulations). However, in scenarios of global GDP shrinkage, the ‘safe’ limit was exceeded in only 14% of simulations. Estimates reported here for total water withdrawals agree closely with similar estimates from the literature, which tend to use more complex methods and models. Similarly, the food production and electricity generation totals can be related to available viable agricultural land or potential CO2 emissions respectively (e.g. through assumptions of future energy generation methods). It is hoped that this work will contribute to the growing global policy and development debate on resource use and sustainable development, particularly through the provision of probabilistic estimates for resource use and by using open-data sources and a relatively simple methodology.

Functional dependencies of soil CO2 emissions on soil biological properties in northern German agricultural soils derived from a glacial till

Agricultural soil CO2 emissions and their controlling factors have recently received increased attention because of the high potential of carbon sequestration and their importance in soil fertility. Several parameters of soil structure, chemistry, and microbiology were monitored along with soil CO2 emissions in research conducted in soils derived from a glacial till. The investigation was carried out during the 2012 growing season in Northern Germany. Higher potentials of soil CO2 emissions were found in grassland (20.40 µg g−1 dry weight h−1) compared to arable land (5.59 µg g−1 dry weight h−1) within the incubating temperature from 5°C to 40°C and incubating moisture from 30% to 70% water holding capacity (WHC) of soils taken during the growing season. For agricultural soils regardless of pasture and arable management, we suggested nine key factors that influence changes in soil CO2 emissions including soil temperature, metabolic quotient, bulk density, WHC, percentage of silt, bacterial biomass, pH, soil organic carbon, and hot water soluble carbon (glucose equivalent) based on principal component analysis and hierarchical cluster analysis. Slightly different key factors were proposed concerning individual land use types, however, the most important factors for soil CO2 emissions of agricultural soils in Northern Germany were proved to be metabolic quotient and soil temperature. Our results are valuable in providing key influencing factors for soil CO2 emission changes in grassland and arable land with respect to soil respiration, physical status, nutrition supply, and microbe-related parameters.

Decomposition of China's CO2 emissions from agriculture utilizing an improved Kaya identity.

In recent decades, China's agriculture has been experiencing flourishing growth accompanied by rising pesticide consumption, fertilizer consumption, energy consumption, etc. and increasing CO2 emissions. Analyzing the driving forces of agricultural CO2 emissions is key requirements for low-carbon agricultural policy formulation and decomposition analysis is widely used for this purpose. This study estimates the agricultural CO2 emissions in China from 1994 to 2011 and applies the Logarithmic Mean Divisia Index (LMDI) as the decomposition technique. Change in agricultural CO2 emissions is decomposed from 1994 to 2011 and includes a measure of the effect of agricultural subsidy. Results illustrate that economic development acts to increase CO2 emissions significantly. Agricultural subsidy acts to reduce CO2 emissions effectively and has increased in recent years. Policy is needed to significantly optimize agricultural subsidy structure and change agricultural development pathway, if China's low-carbon agriculture target is to be achieved. This requires not only decreasing pesticide consumption, fertilizer consumption, energy consumption, etc. but also transformation of China's agricultural development path for optimal outcomes.