Regional CO2 Emissions Research Articles

Comparison of Driving Forces to Increasing Traffic Flow and Transport Emissions in Philippine Regions: A Spatial Decomposition Study

The warming of the climate system has raised a lot of concerns for decades, and this is traceable to human activities and energy use. Conspicuously, the transportation sector is a great contributor to global emissions. This is largely due to increasing dependence on private vehicles and a poorly planned public transportation system. In addition to economic impacts, this also has significant environmental and sustainability implications. This study demonstrates a novel approach using spatial logarithmic mean Divisia index (LMDI) to analyze drivers of traffic flow and its corresponding CO2 emissions in regions through an illustrative case study in the Philippines. Population growth is revealed as the main driver to traffic flow in most regions with the exception of a few regions and the national capital which are driven by economic activity. The economic activity effect shows positive trends contributing positively to traffic flow which is greatly linked to income level rise and increase in vehicle ownership. Concerning the impacts, results revealed that an increase in economic activity generally causes traffic intensity to decrease, and switching to more sustainable modes is not a guarantee to reduce carbon emissions. The authors recommend increasing equity on the appropriation of transport infrastructure projects across regions, quality improvement of public transport services and promoting mixed-use development.

Effect of various shearing shape conditions for the scrap-used coining method on tensile residual stress on sheared edge

Application of high strength steel for automobiles is required to achieve fulfilment of the CO2 emission regulation and improvement of collision safety. Nevertheless, high strength steel has the problem that hydrogen embrittlement and fatigue cracks are likely to occur especially on sheared edge. The previously proposed scrap-used coining method could reduce tensile residual stress on sheared edge using the scrap generated by shearing as the coining tool with a counter punch. However, the conditions this method could reduce tensile residual stress effectively were not clarified. In this report, the effects of the following shearing shape factors on residual stress on sheared edge were investigated, the size of shearing line curvature using punches with a diameter of 10 and 20 mm, positive and negative sign of curvature by testing both of the product and scrap part, and the flat and dome shape of counter punch head. Residual stress on sheared edge could be reduced in the 10 and 20 mm of punch diameter regardless of the product or scrap part. FEM analyses showed that the change of stress distribution in processing area during the scrap-used coining is caused by the shearing hole expansion and reduction and the sheared edge compression by contact of the product and scrap and these mechanisms are common to both of the parts. The dome shaped counter punch is able to reduce the coining load in addition to almost the same amount of residual stress as the flat shaped one. Thus, the tool cost decreases because the cushion pin required to get the reaction force for coining could be reduced.

Optimal Design on Fossil-to-Renewable Energy Transition of Regional Integrated Energy Systems under CO2 Emission Abatement Control: A Case Study in Dalian, China

Optimal design of regional integrated energy systems (RIES) offers great potential for better managing energy sources, lower costs and reducing environmental impact. To capture the transition process from fossil fuel to renewable energy, a flexible RIES, including the traditional energy system (TES) based on the coal and biomass based distributed energy system (BDES), was designed to meet a regional multiple energy demand. In this paper, we analyze multiple scenarios based on a new rural community in Dalian (China) to capture the relationship among the energy supply cost, increased share of biomass, system configuration transformation, and renewable subsidy according to regional CO2 emission abatement control targets. A mixed integer linear programming (MILP) model was developed to find the optimal solutions. The results indicated that a 40.58% increase in the share of biomass in the RIES was the most cost-effective way as compared to the separate TES and BDES. Based on the RIES with minimal cost, by setting a CO2 emission reduction control within 40%, the RIES could ensure a competitive total annual cost as compared to the TES. In addition, when the reduction control exceeds 40%, a subsidy of 53.83 to 261.26 RMB/t of biomass would be needed to cover the extra cost to further increase the share of biomass resource and decrease the CO2 emission.

Emissions of nitrous oxide, dinitrogen and carbon dioxide from three soils amended with carbon substrates under varying soil matric potentials

AbstractCarbon (C) substrates are critical for regulating denitrification, a process that results in nitrous oxide (N2O) and dinitrogen (N2) emissions from soil. However, the impacts of C substrates on concomitant soil emissions of carbon dioxide (CO2) and N2O under varying soil types and soil water contents are not well studied. Three repacked Pallic grassland soils, varying in texture and phosphorus (P) status, containing NO3−‐15N were held at three levels of matric potential (ψ, −3, −5 and −7 kPa), while receiving daily substrate additions (acetate, glucose and water control) for 14 days. The CO2and N2O emissions were measured daily. Additionally, the N2O:(N2 + N2O) ratios were determined using15N on days 3 and 14. Results showed that N2O emissions increased exponentially as soil gas diffusivity declined, and N2O peak emissions were higher with glucose than with acetate addition, with a range (± standard deviation) of 0.1 ± 0.0 to 42.7 ± 2.1 mg N m−2 h−1. The highest cumulative N2O emission (2.5 ± 0.2 g N m−2) was measured following glucose addition with a soilψof −3 kPa. In comparison with added glucose, acetate resulted in a twofold increase in N2emissions in soils with relatively low gas diffusivities. The N2O:(N2O + N2) emissions ratios varied with substrate (glucose, 0.91; acetate, 0.81) on day 3, and had declined by day 14 under substrate addition (≤0.10). Cumulative CO2emissions were enhanced with increasing soil gas diffusivity and were higher for soils amended with glucose (ranging from 22.5 ± 1.3 to 36.6 ± 1.8, g C m−2) than for those amended with acetate. Collectively, the results demonstrate that the increase of N2O, N2and CO2emissions and changes in the N2O:(N2 + N2O) ratio vary over time in response to C substrate type and soil gas diffusivity.HighlightsCo‐regulation of CO2and N2O emissions was assessed for varying soil types and C substrates.Soil diffusivity explained concurrently cumulative N2O and CO2emissions.Acetate enhanced N2O reduction to N2in three grassland soils more than glucose.C substrate effects on soil N2O, N2and CO2emissions were soil type specific.

The inequality of China's regional residential CO2 emissions

Driven by continuous income increases and the urgent need to improve living conditions, CO 2 emissions generated from residential energy consumption have gradually become the main source of China's CO 2 emissions growth. Because of both natural and social factors, China has significant CO 2 emission inequalities, however, there is few literature on residential carbon inequality and its driving factors. Using the provincial panel data of Chinese residential sector from 2005 to 2017, this article examines residential CO 2 emission inequality (carbon inequality) and its driving factors from a static and dynamic perspective to provide empirical support for the formulation of emission reduction policies and the allocation of regional emission reduction quotas. The results indicate that residential carbon inequality grew from 2005 to 2017. The energy intensity disparity was the main contributor in promoting carbon inequality increases, and its effects demonstrated an increasing trend. Per capita income disparity was the second largest factor in the growth of residential carbon inequality, with a contribution of approximately 20%. Additionally, the urban and rural structure also positively widened carbon inequality, but its contribution decreased. Conversely, the energy structure disparity actively facilitated a reduction of carbon inequality, although such active effects were minor. Based on these results, policies relevant narrowing the regional gaps of energy intensity, per capita income, and urbanization were proposed for decreasing carbon inequality of China's residential sector.

The Driving Factors of Carbon Emissions in China’s Transportation Sector: A Spatial Analysis

Studies on the CO2 emissions from the transportation sector in China are increasing, but their findings are inconclusive. The main reason is that the spatial correlation of CO2 emissions from the regional transportation sector has been ignored in examinations of the driving factors of CO2 emissions from this sector. In this paper, new emission factors are adopted to calculate the CO2 emission levels from the transportation sector in Chinese provinces. By fully considering the spatial correlation of regional CO2 emissions and based on a two-way Durbin model incorporating both spatial and temporal fixed effects, the driving factors of CO2 emissions from the transportation sector in China are studied. The CO2 and spatial regression results for the transportation sector in China suggest the following: 1) Most of the regions with the highest CO2 emissions from the Chinese transportation sector are located on the east coast; they have gradually expanded over time to include the central and western regions. 2) The CO2 emissions from the transportation sector are higher in South China than in North China, and the regions with higher CO2 emissions have gradually shifted from north to south. 3) Transportation activity intensity, urbanization level, technological level, industrial structure and per capita GDP greatly impact CO2 emissions from the transportation sector in each province of China. Among these factors, transportation activity intensity, urbanization level, and per capita GDP exert not only direct effects but also indirect effects, whereas technological level and industrial structure exert only direct effects.

Carbon emissions and removals from forests: new estimates, 1990–2020

Abstract. National, regional and global CO2 emissions and removals from forests were estimated for the period 1990–2020 using as input the country reports of the Global Forest Resources Assessment 2020. The new Food and Agriculture Organization of the United Nations (FAO) estimates, based on a simple carbon stock change approach, update published information on net emissions and removals from forests in relation to (a) net forest conversion and (b) forest land. Results show a significant reduction in global emissions from net forest conversion over the study period, from a mean of 4.3 in 1991–2000 to 2.9 Gt CO2 yr−1 in 2016–2020. At the same time, forest land was a significant carbon sink globally but decreased in strength over the study period, from −3.5 to −2.6 Gt CO2 yr−1. Combining net forest conversion with forest land, our estimates indicated that globally forests were a small net source of CO2 to the atmosphere on average during 1990–2020, with mean net emissions of 0.4 Gt CO2 yr−1. The exception was the brief period 2011–2015, when forest land removals counterbalanced emissions from net forest conversion, resulting in a global net sink of −0.7 Gt CO2 yr−1. Importantly, the new estimates allow for the first time in the literature the characterization of forest emissions and removals for the decade just concluded, 2011–2020, showing that in this period the net contribution of forests to the atmosphere was very small, i.e., a sink of less than −0.2 Gt CO2 yr−1 – an estimate not yet reported in the literature. This near-zero balance was nonetheless the result of large global fluxes of opposite sign, namely net forest conversion emissions of 3.1 Gt CO2 yr−1 counterbalanced by net removals on forest land of −3.3 Gt CO2 yr−1. Finally, we compared our estimates with data independently reported by countries to the United Nations Framework on Climate Change, indicating close agreement between FAO and country emissions and removals estimates. Data from this study are openly available via the Zenodo portal (Tubiello, 2020), with DOI https://doi.org/10.5281/zenodo.3941973, as well as in the FAOSTAT (Food and Agriculture Organization Corporate Statistical Database) emissions database (FAO, 2021a).

Corrigendum: Extrapolation and Uncertainty Evaluation of Carbon Dioxide and Methane Emissions in the Qinghai-Tibetan Plateau Wetlands Since the 1960s

Wetlands are important modulators of atmospheric greenhouse gas (GHGs) concentrations. However, little is known about the magnitudes and spatiotemporal patterns of GHG fluxes in wetlands on the Qinghai-Tibetan Plateau (QTP), the world’s largest and highest plateau. In this study, we measured soil temperature and the fluxes of carbon dioxide (CO2) and methane (CH4) in an alpine wetland on the QTP from April 2017 to April 2019 by the static chamber method, and from January 2017 to December 2017 by the eddy covariance (EC) method. The CO2 and CH4 emission measurements from both methods showed different relationships to soil temperature at different timescales (annual and seasonal). Based on such relationship patterns and soil temperature data (1960-2017), we extrapolated the CO2 and CH4 emissions of study site for the past 57 years: the mean CO2 emission rate was 1096.59 mg C m-2 h-1 on different measurement methods and timescales, with the range of the mean emission rate from 421.17 to 1754.99 mg C m-2 h-1, while the mean CH4 emission rate was 32.99 mg C m-2 h-1, with the ranges of the mean emission rate from 16.95 to 46.25 mg C m-2 h-1. The estimated regional CO2 and CH4 emissions from permanent wetlands on the QTP were 94.29 and 2.37 Tg C year-1, respectively. These results indicate that uncertainties caused by measuring method and timescale should be fully considered when extrapolating wetland GHG fluxes from local sites to the regional level. Moreover, the results of global warming potential showed that CO2 dominates the GHG balance of wetlands on the QTP.

Hydrological, geochemical and land use drivers of greenhouse gas dynamics in eleven sub-tropical streams

Greenhouse gas (GHG) emissions from freshwater streams are poorly quantified in sub-tropical climates, especially in the southern hemisphere where land use is rapidly changing. Here, we examined the distribution, potential drivers, and emissions of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) from eleven Australian freshwater streams with varying catchment land uses yet similar hydrology, geomorphology, and climate. These sub-tropical streams were a source of CO2 (74 ± 39 mmol m−2 day−1), CH4 (0.04 ± 0.06 mmol m−2 day−1), and N2O (4.01 ± 5.98 µmol m−2 day−1) to the atmosphere. CO2 accounted for ~ 97% of all CO2-equivalent emissions with CH4 (~ 1.5%) and N2O (~ 1.5%) playing a minor role. Episodic rainfall events drove changes in stream GHG due to the release of soil NOx (nitrate + nitrite) and dissolved organic carbon (DOC). Groundwater discharge as traced by radon (222Rn, a natural groundwater tracer) was not an apparent source of CO2 and CH4, but was a source of N2O in both agricultural and forest catchments. Land use played a subtle role on greenhouse gas dynamics. CO2 and CH4 increased with catchment forest cover during the wet period, while N2O and CH4 increased with agricultural catchment area during the dry period. Overall, this study showed how DOC and NOx, land use, and rainfall events interact to drive spatial and temporal dynamics of GHG emissions in sub-tropical streams using multiple linear regression modelling. Increasing intensive agricultural land use will likely decrease regional CO2 and CH4 emissions, but increase N2O.

Assessing energy poverty and its effect on CO2 emissions: The case of China

With scholars paying increasing attention to the environmental effects of energy poverty, further discussion on the energy poverty-CO2 nexus is particularly useful for achieving carbon reduction targets from the perspective of energy poverty. Accordingly, this paper investigates the dynamic impact of energy poverty on CO2 emissions in China. By proposing a new and comprehensive evaluation index, we assess the energy poverty levels in 30 Chinese provinces for the period 2002–2017. Then, we re-estimate the impact of energy poverty on CO2 emissions using the system-generalized method of moments (SYS-GMM) method. We find that although significant differences exist in energy poverty across various regions in China, the country's total level of energy poverty displays a downward trend over the period 2002–2017. Furthermore, energy poverty can accelerate the growth of CO2 emissions in China. In regions with high-level energy poverty, a bidirectional causal link exists between energy poverty and CO2 emissions, while a unidirectional causality runs from energy poverty to CO2 emissions in regions with low-level energy poverty. The findings of this paper, therefore, add to the existing literature and provide important policy implications for curbing CO2 emissions.

CO2 emissions from the electricity sector during China's economic transition: from the production to the consumption perspective

Abstract China's economy has entered the ‘New Normal’ era, transferring from the fast growth to the medium-high growth with ambitious targets on climate change mitigation and pollution alleviation. As the largest CO2 source among all industrial sectors, the electricity sector plays an important role in China's recent stagnating CO2 emissions and achieving mitigation targets. Here we estimate CO2 emissions from electricity production by using up-to-date emission factors and calculate the CO2 emissions embodied in purchased electricity using the Quasi-Input-Output (QIO) model. In addition, we quantify the drivers of CO2 emissions from electricity production and consumption using the index and structural decomposition analysis. Our results show that China's economic transition and increasing electricity intensity largely contributed to the growth of CO2 emissions in the electricity sector, while the improvement of energy efficiency, non-fossil fuel substitution, and shrinking share of industrial output reduced CO2 emissions. The consumption-based CO2 emissions in developed regions in China are higher than their production-based CO2 emissions in 12 provinces. The recent slowing down of economic growth, energy transition, improved efficiency, non-fossil fuel substitution, and electricity trade have altered the CO2 trajectory in the electricity sector since 2008 global financial crisis. This study could help policymakers better understand CO2 emissions in the electricity sector and formulate effective policies to decarbonize the electricity sector in the future.

Has processing trade made China's exports cleaner? A regional level analysis

This paper investigates the role of processing trade on China’s regional CO2 emission intensity of exports (EIE). We investigate the temporal changes in regional EIEs and their determinants from 2002 to 2012 by using special multi-regional input-output tables that distinguish the production of processing exports from other production at the regional level. By using structural decomposition analysis, we attribute the regional EIE changes into effects of very detailed components, which show the roles of different production types and factors in EIE changes. We find that EIE increased from 2002 to 2007 but decreased from 2007 to 2012. In this regard, processing exports play a decisive role in the first period, making China's exports dirtier, but help exports be cleaner after the crisis. By factor, the input structure reflected by the inter-industry production linkage is the main reason for the different performances of EIEs in the two periods. The interregional trade in intermediate inputs has increased most inland regions' EIEs while decreasing coastal regions' EIEs. • The EIE for most regions firstly significantly increased from 2002 to 2007, and then decreased from 2007 to 2012. • Processing exports play a key role in EIE changes. Their changes increased EIE first and then decreased it. • The effect of input structure is dominant in the total effect of processing exports, with other factors played limited roles. • The different change in the commodity structure of intermediate inputs is the main reason for different performances of EIE before and after the crisis. • The increasing interregional trade has exacerbated the regional inequality in terms of environmental cost from exports.

Spatial Analysis of an Emission Inventory from Liquefied Natural Gas Fleet Based on Automatic Identification System Database

Many states are actively working toward regulating CO2 emissions from a wide range of industries. However, due to the international characteristic of shipping, the emissions from shipping have not yet been strictly controlled. Using Automatic Identification System (AIS) data acquired through satellites, this study estimates the emission inventory, such as, CO2, CH4, CH4, N2O, NOx, CO and non-methane volatile organic compounds (NMVOCs) around the world and bunker consumption from a liquified natural gas (LNG) fleet under the assumption that a LNG fleet uses LNG as fuel. Using position data calculated from an AIS database, we made comparisons regarding the LNG trade amount and bunker consumption of LNG fleet, as well as the total CO2 inventory and CO2 emissions from LNG fleet in the vicinity of the coasts of relevant countries. The result provides insights into (1) how the emissions and bunker consumption from LNG fleet is distributed, (2) which countries are taking relatively more advantages of LNG trade, and (3) which countries are suffering possible harmful effects.

Regional CO2 impact assessment of road infrastructure improvements

Transparent methods of estimating CO2 emissions from transportation sources are necessary to evaluate mitigation strategies. This study proposes a framework to assess the regional impact of roadway designs on CO2 emissions. First, three roadway infrastructure configurations were designed to improve the traffic flow at intersections and interchanges. Second, the economical and environmental life-cycle cost assessments of constructing and maintaining new infrastructures were developed. Then, the effects of infrastructure on regional vehicle CO2 emissions were modeled using a simulation-based dynamic traffic assignment model coupled with the U.S. Environmental Protection Agency's MOtor Vehicle Emission Simulator (MOVES) model. The case study estimated that converting 72 stop signs to roundabouts within El Paso, TX, reduced daily vehicular CO2 emissions by more than 50 tonnes, paying back the CO2 from construction and maintenance within 2.5 to 2.9 years. The roundabout modifications' cost-effectiveness ranged from $30 to $130 per tonne of CO2 over a 30-year assessment.

The impact of LCTI on China's low-carbon transformation from the spatial spillover perspective.

China has conducted a long-term low-carbon technology innovation (LCTI), but there was a faster increase of CO2 emission in 2017 and 2018 than in 2016, which has lead scholars to doubt the effect of LCTI on CO2 emission. This paper builds a spatial auto regression (SAR) model with provincial panel data from 2011 to 2017 to calculate the spatial spillover effect of China's LCTI on regional CO2 emission. The results show that regional LCTI can reduce the local CO2 emission, but will increase the CO2 emission of adjacent regions due to spatial spillover effect. This produces the uncertainty of the promotion effect of LCTI on China's low-carbon transformation. Therefore, this paper suggests innovation resources should be appropriately and evenly distributed among regions to avoid their agglomeration in few regions.

Uncovering CO2 emission drivers under regional industrial transfer in China’s Yangtze River Economic Belt: a multi-layer LMDI decomposition analysis

With the relocation of heavy industries moving from downstream region to upstream and midstream regions in the Yangtze River Economic Belt (YREB), it is critical to encourage coordinated low carbon development in different regions within the YREB. This paper uncovers the evolution of CO2 emissions in different regions within the YREB for the period of 2000–2017. It decomposes regional CO2 emission changes using the temporal and cross-regional three-layer logarithmic mean Divisia index (LMDI) method. Besides, it decomposes industrial CO2 emission changes using the temporal two-layer LMDI method. The research results show that economic growth is the major driver for regional CO2 emission disparities. The mitigation drivers, such as energy intensity and energy structure, lead to a more decreased CO2 emission in the downstream region than in the upstream and midstream regions. In addition, it proposes several policy recommendations based upon the local realities, including improving energy efficiency, optimizing energy structure, promoting advanced technologies and equipment transfers, and coordinating the development in the upstream, midstream and downstream regions within the YREB.

Evolutionary Algorithm for the Electric Vehicle Routing Problem with Battery Degradation and Capacitated Charging Stations

As CO2 emission regulations increase, fleet owners increasingly consider the adoption of Electric Vehicle (EV) fleets in their business. The conventional Vehicle Routing Problem (VRP) aims to find a set of routes to reduce operational costs. However, route planning of EVs poses different challenges than that of Internal Combustion Engine Vehicles (ICEV). The Electric Vehicle Routing Problem (E-VRP) must take into consideration EV limitations such as short driving range, high charging time, poor charging infrastructure, and battery degradation. In this work, the E-VRP is formulated as a Prognostic Decision-Making problem. It considers customer time windows, partial midtour recharging operations, non-linear charging functions, and limited Charge Station (CS) capacities. Besides, battery State of Health (SOH) policies are included in the E-VRP to prevent early degradation of EV batteries. An optimization problem is formulated with the above considerations, when each EV has a set of costumers assigned, which is solved by a Genetic Algorithm (GA) approach. This GA has been suitably designed to decide the order of customers to visit, when and how much to recharge, and when to begin the operation. A simulation study is conducted to test GA performance with fleets and networks of different sizes. Results show that E-VRP effectively enables operation of the fleet, satisfying all operational constraints.

Estimating the net costs of brine production and disposal to expand pressure-limited dynamic capacity for basin-scale CO2 storage in a saline formation

If carbon capture and storage (CCS) needs to be deployed at basin- or larger-scale, it is likely that multiple sites will be injecting carbon dioxide (CO2) into the same geologic formation. This could lead to excessive pressure buildup, overlapping induced pressure fronts, and pressure interference with neighboring uses of the subsurface. Extracting the in situ brine from the storage formation could be necessary to relieve pressure constraints; control migration of the CO2 plume, displaced brine, and the induced pressure front; and sequester more CO2 while reducing potential risks. Such active pressure management could be very costly, and it could present a formidable economic constraint on the feasible scale of deployment of CCS. Alternatively, there may be high-injectivity zones (“storage sweet spots”) where a significant volume of CO2 could be stored without producing brine. For simulated deployment of CO2 storage sites across the Illinois Basin, the results of this study suggest that brine production could be required to sequester 20 % or more of the regional CO2 emissions of major stationary sources in the Mount Simon Sandstone saline formation. In some cases, brine production could expand pressure-limited CO2 storage capacity enough to more than compensate for the additional costs of pressure management, but only if produced brine could be cheaply reinjected onsite for disposal in an overlying geologic formation. With or without brine production, this study found that the lowest-cost deployment option was to inject CO2 only into a potential storage sweet spot of the Mount Simon Sandstone.

Decomposition of driving factors of industry-related CO2 emissions and its decoupling with economic growth in Fujian Province, China

The emission of CO2 from major sectors and key industries are the predominant sources of regional CO2 emissions. It is the prerequisite to promote sectoral carbon emissions reduction, to cla-rify their influencing factors and investigate their relationship with regional economic growth. It is also of great significance for the implementation of regional total carbon emissions control. Using the Logarithmic mean Divisia index method (LMDI) and the Tapio decoupling model, we analyzed the driving factors, and decoupling status with economic growth of 13 major carbon emissions industries in Fujian Province from 1997 to 2017. The results showed that the electricity and heat production and supply industry was the major source of CO2 emissions in Fujian Province, with an increase of 101.74 Mt (from 18.89 Mt to 120.63 Mt) during the period 1997 to 2017. The top three industries with the fastest annual growth rate in CO2 emissions were non-ferrous metal smelting and rolling processing industry (18.1%), textile industry (12.1%), and ferrous metal smelting and rolling processing industry (12.1%). Among the influence factors for the changes in carbon emissions in 13 major industries, economic growth effect and population scale effect were the main positive driving factors, while the restraining effects of energy structure, energy intensity, and industrial structure were continuously increasing. In terms of decoupling relationship, the decoupling index between economic growth and industry-related CO2 emissions showed a downward trend on the whole. Since the 11th Five-Year-Plan period, some industries had begun to show strong decoupling to some extent. The farming, forestry, animal husbandry, fishery and water conservancy industry exhibited expansive negative decoupling, whereas the electricity and heat production and supply industry exhibited weak negative decoupling during 13th Five-Year Plan period. The effects of energy structure and energy intensity had substantial impacts on the decoupling with economic growth for various industries. The industrial structure effect had a smaller impact on the decoupling with economic growth, while the population scale effect had almost no impact.

Rainfall possibly disturbs the diurnal pattern of CO2 degassing in the Lijiang River, SW China

Estimates of CO2 flux from rivers are uncertain due to limited measurements at high-resolution. In addition, precipitation may impact diurnal variation of riverine CO2 flux but the processes controlling those impacts are unknown. Here, we examine the diurnal characteristics of some physicochemical parameters, meteorological parameters, water level, δ13CDIC values, and the CO2 emission flux at two transects (DM and PY) of a typical karst river (Lijiang River, LJR), southwest China, during May 13–16, 2017. Our results show significant correlations between CO2 flux, DO, pCO2, and δ13CDIC and reflect control of CO2 flux diel pattern (decreasing during daytime and increasing at night) by metabolic processes of aquatic plants. The amplitude of CO2 flux diel pattern is weakened at DM. In contrast, diurnal pattern are interrupted at PY by the precipitation, and afterwards controlled by water level due to the significant positive correlation between water level and CO2 flux. Certainly, this amplitude will return to prestorm values as the water level recovered. We suggest that effects of precipitation on regional CO2 efflux estimate require scaling water level and CO2 flux with a linear relationship, and converting hourly flux to daily flux (α values) to improve the estimate of CO2 flux diel cycle. These methods will optimize sampling monitoring strategies and provide more reliable estimates of regional riverine CO2 emissions.