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This paper investigates the relationship between CO2 emissions, energy consumption, economic growth, and foreign direct investment for a sample of Asia-Pacific Economic Cooperation Countries (APEC) countries from 1981:Q1 to 2021:Q1 employing panel data methodology. We identify cross-sectional dependence and hence utilize the cross-sectional augmented Dickey-Fuller panel unit root test for appropriate estimation. The cointegration test developed by Westerlund (2008) reveals a long-run equilibrium between CO2 emissions, energy consumption, economic growth, and foreign direct investment. Long-run parameter estimates based on Common Correlated Effect Mean Group indicate that an increase in FDI inflows has a negative impact on air quality, supporting the pollution haven hypothesis. The cointegration test results also show that the impact of Gross Domestic Product (GDP) on CO2 emissions varies by country in the estimation sample. In contrast to the mixed evidence on the effects of other variables, the increase in energy consumption is positively and significantly affecting CO2 emissions in all APEC countries. Emirmahmutoglu and Kose Econ Model 28:870-876, (2011)'s panel causality test results show a bidirectional relationship between FDI and CO2 emissions in Japan. Furthermore, there is a bidirectional causal relationship between GDP and energy consumption in Australia, China, Japan, and Singapore. Overall, empirical evidence suggests that APEC countries should adhere to strict regulations and invest in environmental-friendly clean technologies to attract foreign direct investment.

This paper is effectively a scenario analysis of the energy system of Bosnia and Herzegovina (BiH) from the perspective of the possible future reduction of greenhouse gas (GHG) emissions in the power generation sector, with the aim to become climate neutral by 2050, in compliance with the Green Agenda for the Western Balkan. According to the data from 2016, the share of power generation in the total GHG emissions in BiH was approximately 50%. By using the LEAP (Long-range Energy Alternatives Planning) energy model, two scenarios—the “gradual transition scenario” and the “climate neutral” scenario—have been analyzed for the period 2018–2050, and each scenario included decarbonization measures such as the extensive use of Renewable Energy Sources (RES). Unlike the climate neutral scenario, the gradual transition scenario includes the replacement of certain parts of the old, currently-in-operation Coal-fired Power Plants (CFPPs) with the new CFPP, which is more efficient. In the climate-neutral scenario, that part of the existing CFPPs is replaced by a mix of RESs. The results from the first scenario suggest that the share of CFPPs in electricity generation has gradually decreased from 69.3% to 16.3% in 2050, and CO2 emissions from the power generation sector in 2050 will be 2.2 million tons—roughly 83.5% less than in 2014. According to the second scenario, the emphasis is strongly on the growth and promotion of RESs, which have significantly taken over the roles of major producers of electricity, encouraging the low-carbon development of BiH. Analysis results show that, in 2050, there will be no CO2 emissions from power generation. It can be concluded that specifically designed energy models for the optimization of capacities and CO2 emissions through convergence towards RESs could be an optimistic and promising option for BiH to become climate neutral while meeting increasing energy demands. The results show the required RES capacities needed for achieving climate-neutral power generation by 2050, with the current rate level of power generation. Based on the results, RES investment needs can be estimated. Overall, the results of the scenarios can be used for the strategic planning of the power generation sector in BiH until 2050.

We employ an ARDL bounds testing approach to cointegration and Unrestricted Error Correction Models to estimate the relationship between income and CO2 emissions per capita in 21 Latin American Countries (LACs) over 1960–2017. Using time series, we estimate six different specifications of the model to take into account the independent effect on CO2 emissions per capita of different factors considered as drivers of different dynamics of CO2 emissions along the development path. This approach allows to address two concerns. First, the estimation of the model controlling for different variables serves to assess if the EKC hypothesis is supported by evidence in any of the LACs considered and to evaluate if this evidence is robust to different model specifications. Second, the inclusion of control variables accounting for the effect on CO2 emissions is directed at increasing our understanding of CO2 emissions drivers in different countries. The EKC hypothesis effectively describes the long-term income-emissions relationship only in a minority of LACs and, in many cases, the effect on CO2 emissions of different factors depends on the individual country experience and on the type and quantity of environmental policies adopted. Overall, these results call for increased environmental action in the region., Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature

Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO2 emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact. Publisher's Version

The scientific literature contains contrasting findings about the climate effects of forest bioenergy, partly due to the wide diversity of bioenergy systems and associated contexts, but also due to differences in assessment methods. The climate effects of bioenergy must be accurately assessed to inform policy‐making, but the complexity of bioenergy systems and associated land, industry and energy systems raises challenges for assessment. We examine misconceptions about climate effects of forest bioenergy and discuss important considerations in assessing these effects and devising measures to incentivize sustainable bioenergy as a component of climate policy. The temporal and spatial system boundary and the reference (counterfactual) scenarios are key methodology choices that strongly influence results. Focussing on carbon balances of individual forest stands and comparing emissions at the point of combustion neglect system‐level interactions that influence the climate effects of forest bioenergy. We highlight the need for a systems approach, in assessing options and developing policy for forest bioenergy that: (1) considers the whole life cycle of bioenergy systems, including effects of the associated forest management and harvesting on landscape carbon balances; (2) identifies how forest bioenergy can best be deployed to support energy system transformation required to achieve climate goals; and (3) incentivizes those forest bioenergy systems that augment the mitigation value of the forest sector as a whole. Emphasis on short‐term emissions reduction targets can lead to decisions that make medium‐ to long‐term climate goals more difficult to achieve. The most important climate change mitigation measure is the transformation of energy, industry and transport systems so that fossil carbon remains underground. Narrow perspectives obscure the significant role that bioenergy can play by displacing fossil fuels now, and supporting energy system transition. Greater transparency and consistency is needed in greenhouse gas reporting and accounting related to bioenergy.

China’s strategy of greening industrial development aims to decouple industrial growth from industrial wastewater discharges (IWDs). This study combines decoupling analysis, decomposition analysis, and attribution analysis to support this goal. First, the decoupling analysis is employed to explore the degree of decoupling between industrial growth and IWDs in China, as well as across 30 provinces, from 2000 to 2015. Next, a decomposition analysis focusing on the change in industrial wastewater discharge intensity (IWDI) is performed to reveal the factors influencing decoupling trends. Then, attribution analysis is used to attribute contributions of these factors to different regions. Our decoupling results indicate an increasing decoupling trend between industrial output and IWDs in China in the past 15 years. Meanwhile, there is a convergence in decoupling degrees among provinces. Decomposition results reveal that water intensity plays a dominant role in promoting decoupling, while the wastewater discharge coefficient negatively impacted decoupling before 2005 but contributed to decoupling later on. Regional attribution results indicate provinces in South China have exerted more efforts in both water saving and wastewater treatment during the study period. Water scarce provinces in North China performed better in terms of water saving, while more developed and water-rich provinces in South China performed better in wastewater treatment. This paper suggests targeted policy methods at province level.

The transportation sector is one of the main contributors to global greenhouse gas (GHG) emissions. As the efforts towards emission mitigation increase, the expectation from the sector arises equally. In this analysis, the transportation sector of Turkey is studied to shed light on the future based on historical realizations. In this respect, the Logarithmic Mean Divisia Index (LMDI) method is used to assess and reveal the influential factors on CO2 emissions in the sector between 2000 and 2017. The emission intensity of the sector and fuel switching shows promising trends from 2000 through 2010, whereas growing preference for SUVs challenges emission reductions between 2010 and 2017. The results indicate that i) The transportation sector CO2 emissions are mainly driven upwards by economic growth, followed by population and emission intensity effects from 2000 to 2017 ii) The overall impact of transportation intensity shows significant reduction potential iii) Fuel switching incentives and fleet efficiency have a positive effect on emission mitigation from 2000 through 2010. However, this gain is reduced due to the rising popularity of SUVs in the rest of the analysis period. In this respect, CO2 emission mitigation in the transportation sector necessitates 1) careful planning of demand management for freight transportation including master designs production/manufacturing sites, material flows, and demand points coupled with economic activities 2) passenger transportation measures to reduce passenger car travel including zoning for public transit corridors, improved public transportation system 3) well-structured incentives on energy-efficient cars and clean energy technologies such as electric vehicles to convince individuals. Analysis can be generalized on a global scale due to the similar dynamics inherent in the sector. Publisher's Version

Document Information Language:English Accession Number: WOS:000534865700002 PubMed ID: 32445148, This study is primarily motivated by exploring the role of globalization, energy intensity over economic expansion, and its impact on environmental sustainability in China. To this end, a sequence of econometrics tests were conducted to address this hypothesized relationship. The choice of China is informed by intense industrial activities and being one of the leading world economies. Annual frequency data from 1971 to 2015 is utilized for the current study. Empirical finding from novel and robust Bayer and Hanck combined cointegration test supports cointegration equilibrium relationship among the variables under review. This indicates a convergence between the explanatory variable and the explained variable in the fitted model. Further empirical evidence shows a positive statistically significant relationship between real income, ecological footprint, and globalization index. This outcome is insightful for environmental economists and policymakers. The causality analysis supports the growth-induced energy consumption hypothesis. Based on these revelations, policy direction for the energy sector in China in the face of global interconnectedness is offered in the concluding remark of this study.

The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.

Document Information Language:English Accession Number: WOS:000518367800103 PubMed ID: 32123762, In this era of intensive electricity utilization for economic development, the role of urbanization remains inconclusive, especially in developing economies. Here, this study examined the electricity consumption and economic growth nexus in a trivariate framework by incorporating urbanization as an additional variable. Using the recent novel Maki cointegration test, Ng-Perron, Zivot-Andrews, and Kwiatkowski unit root tests along with FMOLS, DOLS and the CCR estimation methods, we relied on an annual frequency data from 1971-2014. Results from FMOLS, DOLS and the CCR regression confirms the electricity consumption-driven economic growth. This is desirable as Nigeria is heavily dependent on energy (electricity) consumption. A unidirectional causality from urbanization to electricity consumption and economic growth was found but the long-run empirical findings revealed urbanization impedes growth-a situation that has policy implications. The study highlights that though urbanization is a good predictor of Nigeria's economic growth, however, the adjustment of the energy portfolio to meet the growing urban demand will curtail the adverse and far-reaching impact of urbanization on the economy., SA Sarkodie acknowledges the financial support of Nord University Business School, Bodo, Norway.

Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders were closed and populations were confined to their homes, which reduced transport and changed consumption patterns. Here we compile government policies and activity data to estimate the decrease in CO2 emissions during forced confinements. Daily global CO2 emissions decreased by –17% (–11 to –25% for ±1σ) by early April 2020 compared with the mean 2019 levels, just under half from changes in surface transport. At their peak, emissions in individual countries decreased by –26% on average. The impact on 2020 annual emissions depends on the duration of the confinement, with a low estimate of –4% (–2 to –7%) if prepandemic conditions return by mid-June, and a high estimate of –7% (–3 to –13%) if some restrictions remain worldwide until the end of 2020. Government actions and economic incentives postcrisis will likely influence the global CO2 emissions path for decades.

Document Information Language:English Accession Number: WOS:000514544700006 PubMed ID: 32019050, Given that the European Union-28 countries proposed a target of 3% of the Gross Domestic Product on research and development (R&D) expenditure by 2020, the current study attempts to examine the role of R&D on environmental sustainability. In addition, the study further investigates the long-run and causal interaction between, renewable energy consumption, nonrenewable energy consumption, and economic growth in an ecological footprint-income function. Notably, the study incorporates research and development (R&D) expenditure to the model as an additional variable, and measures impact of each variable on ecological footprint. Empirical evidence is based on a balanced panel data between annual periods of 1997-2014 for selected EU-16 countries. The Pedroni, Johansen Multivariate and Kao tests all reveal a cointegration between ecological footprint, economic growth, research and development expenditure, renewable, and nonrenewable energy consumption. The Fully Modified and Dynamic Ordinary Least Squares models (FMOLS and DOLS) both suggest a negative significant relationship between the countries' research and development expenditure and ecological footprint in the long-run. This implies that spending on R&D significantly impacts on environmental sustainability of the panel countries. Our study affirms that nonrenewable energy consumption and economic growth increase carbon emission flaring while renewable energy consumption declines ecological footprint. The panel causality analysis reveals a feedback mechanism between ecological footprint. R&D expenditure, renewable, and nonrenewable energy consumption. We further observed a one-way causality between ecological footprint and economic growth. The current further validates that the Environmental Kuznet Curve Hypothesis (EKC) holds for this panel of EU countries examined. Effective policy implications could be drawn toward modern and environmentally friendly energy sources, especially in attaining the Sustainable Development Goals via spending on R&D.

While most African economies are primarily sandwiched with the seemingly unsurmountable task of attaining consistent economic growth and unhindered energy supply, the enormous threat posed by environmental degradation has further complicated the economic and environmental sustainability drive. In this context, the present study examines the effect of economic growth, urbanization, electricity consumption, fossil fuel energy consumption, and total natural resources rent on pollutant emissions in Africa over the period 1980-2014. By employing selected African countries, the current study relies on the Kao and Pedroni cointegration tests to cointegration analysis, the Pesaran’s Panel Pooled Mean Group-Autoregressive distributive lag methodology (ARDL-PMG) for long run regression while Dumitrescu and Hurlin (2012) is employed for the detection of causality direction among the outlined variables. The study traces long run equilibrium relationships b-etween examined indicators. The ARDL-PMG results suggest a statistical positive relationship between pollutant emissions and urbanization, electricity consumption and non-renewable energy consumption. Dumitrescu and Hurlin (2012) Granger causality test lends support to the long-run regression results. Bi-directional causality is observed between pollutant emissions, electricity consumption, economic growth and pollutant emissions while a unidirectional causality is apparent between total natural resources rent and pollutant emissions. Based on these results, several policy implications for the African continent were suggested. (a) The need for a paradigm shift from fossil fuel sources to renewables is encouraged in the region (b) The need to embrace carbon storage and capturing techniques to decouple pollutant emissions from economic growth on the continent’s growth trajectory. Further policy insights are elucidated.

Many inland waters exhibit complete or partial desiccation, or have vanished due to global change, exposing sediments to the atmosphere. Yet, data on carbon dioxide (CO2) emissions from these sediments are too scarce to upscale emissions for global estimates or to understand their fundamental drivers. Here, we present the results of a global survey covering 196 dry inland waters across diverse ecosystem types and climate zones. We show that their CO2 emissions share fundamental drivers and constitute a substantial fraction of the carbon cycled by inland waters. CO2 emissions were consistent across ecosystem types and climate zones, with local characteristics explaining much of the variability. Accounting for such emissions increases global estimates of carbon emissions from inland waters by 6% (~0.12 Pg C y−1). Our results indicate that emissions from dry inland waters represent a significant and likely increasing component of the inland waters carbon cycle., Many inland waters seasonally or permanently dry up, thus exposing sediments to the atmosphere. Here the authors show that a substantial amount of CO2 is emitted from these dry sediments, increasing current inland water carbon flux estimates by 6%.

Understanding the convergence of energy intensity helps in assessing whether policies targeted at reducing energy intensity are effective and should thus be continued or reinforced. This paper analyzes the convergence of cross-province energy intensity in China based on panel data of 29 provinces for the period 2003–2015 by means of sigma convergence, kernel density analysis, and unconditional and conditional beta convergence. The empirical results show that the omission of spatial spillovers underestimates conditional beta convergence. We thus argue that the implementation of effective policy for reducing energy intensity depends not only on the driving forces in the own province but also on the spatial spillover effects in neighboring provinces, particularly technology transfer, knowledge spillovers, and the input-output relationship. From the analysis, it follows that adopting low-energy capital, attracting more FDI inflows and developing indigenous innovation capabilities are major policy handles.

To put the brakes on global climate change, China, the world's top emitter, has established ambitious CO2 emissions reduction targets. Industry-level emissions analysis can help policymakers determine better ways to achieve mitigation targets. This study is the first to target the total-factor carbon emission performance (TCPI) of secondary and service industries. We first compile industry-level CO2 emission inventories of 25 Yangtze River Delta cities during 2007–2016. The TCPI of secondary and service industries is then estimated by the non-radial directional distance function. We then compare the TCPI of the two industries across levels, dynamics, and inequalities using a global metafrontier approach. The results show the TCPI of the service industry (0.563 in 2016) was significantly higher than that of secondary industry (0.256 in 2016), suggesting that the service industry was more carbon-friendly. The TCPI gap between the secondary and service industries narrowed over the study period. The TCPI of secondary industry showed a promising increase during 2007–2016 with an annual growth rate of 2.30%, reflecting the positive effects of the government's reforms and environmental regulations. By contrast, the service industry saw a downward trend in TCPI, decreasing by 1.68% annually, primarily because it is a newcomer to low-carbon development. TCPI inequality in secondary industry was much larger than in the service industry, suggesting that significant heterogeneity exists in secondary industry. Therefore, policymakers should implement targeted mitigation policies for secondary industry, and place decarbonising the service industry on the agenda to reverse its decreasing TCPI.

Accession Number: WOS:000515816200008 PubMed ID: 32006332, The path to sustainable economic growth and development has preoccupied most economies and the European Union (EU) member countries is no exception. Thus, the current study is aimed at revisiting the energy-induced growth by disaggregating energy consumption into (renewable and non-renewable energy consumption) as means of growth. Also, the role of research and development (R&D) in the attainment of sustainable growth in the panel of EU countries over the period 1997-2014 is examined. Accordingly, the preliminary investigation revealed a significant evidence of cointegration in the panel of estimated variables. The study also expectedly suggests that 1% increase in non-renewable energy consumption, renewable energy consumption, and R &D in the long-run is responsible for a respective increase of 0.60%, 0.13%, and 0.05 in the panel countries growth. Furthermore, the causality evidence from renewable energy consumption to economic growth is not only significant but is observed in more countries than the causality from non-renewable energy consumption to economic growth. Thus, it implies that the commitment to sustainable growth and climate actions of the EU countries is fact yielding desirable outcome. Similarly, research development is observed to play a significant and causality impact on the economic growth of the panel countries. In general, the study posits an interesting and a potentially effective policy outlook and economic perspective for the bloc countries.

Reaching the European Union's 2030 targets for primary energy use (PE) and CO2 emissions (CE) requires an accurate assessment of how different technologies perform on these two fronts. To calculate the PE and CE associated with the consumption of electricity (e.g. by an electric vehicle or a heat pump) conversion factors (CFs) are required, namely a primary energy factor and a CO2 intensity factor. Previous theoretical work has shown that the calculation and use of CFs is a contentious and multifaceted issue, but a review of the actual practice in academic literature has so far been missing. 110 recent studies have been systematically reviewed across six methodological aspects, to find that 75% of the studies consider only a single country, 79% apply a purely retrospective perspective, 66% apply a yearly temporal resolution, 75% apply a purely operational (instead of a life-cycle) perspective, 85% make use of average (rather than marginal) CFs, and 77% ignore electricity imports from surrounding countries. Future research in which CFs are used should more carefully consider each of these methodological aspects and explicitly justify the choices that are being made on this front. There is also a strong need in the literature for a publicly available and methodologically transparent database of up-to-date CFs, which would not only enable more accurate and transparent PE and CE calculations, but also support the further development of building energy performance assessment methods and smart grid algorithms.

Global greenhouse gas (GHG) emissions can be traced to five economic sectors: energy, industry, buildings, transport and AFOLU (agriculture, forestry and other land uses). In this topical review, we synthesise the literature to explain recent trends in global and regional emissions in each of these sectors. To contextualise our review, we present estimates of GHG emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions. Overall, the literature and data emphasise that progress towards reducing GHG emissions has been limited. The prominent global pattern is a continuation of underlying drivers with few signs of emerging limits to demand, nor of a deep shift towards the delivery of low and zero carbon services across sectors. We observe a moderate decarbonisation of energy systems in Europe and North America, driven by fuel switching and the increasing penetration of renewables. By contrast, in rapidly industrialising regions, fossil-based energy systems have continuously expanded, only very recently slowing down in their growth. Strong demand for materials, floor area, energy services and travel have driven emissions growth in the industry, buildings and transport sectors, particularly in Eastern Asia, Southern Asia and South-East Asia. An expansion of agriculture into carbon-dense tropical forest areas has driven recent increases in AFOLU emissions in Latin America, South-East Asia and Africa. Identifying, understanding, and tackling the most persistent and climate-damaging trends across sectors is a fundamental concern for research and policy as humanity treads deeper into the Anthropocene.

The authors adopt a new approach to modeling the relationship between emissions and income using long-run per capita growth rates. This approach allows them to test multiple hypotheses about the drivers of per capita emissions in a single framework and avoid several of the econometric issues that have plagued the environmental Kuznets curve literature. They estimate models for carbon and sulfur dioxide emissions. They can reject restricted models that omit either growth or beta convergence effects. Although the term representing the environmental Kuznets effect is statistically significant for per capita carbon and sulfur dioxide emissions, the estimated income per capita turning points are out of the sample for the full data set.

City-level CO2 emission accounting is necessary to identify the different energy circumstances among all cities. However, due to a lack of data, energy consumption and emission statistics are not well documented. Focusing on the industrial production using fossil fuels, our work provides the first detailed city-level estimation of production-based sectoral CO2 emissions in the Xinjiang Uygur Autonomous Region. In 2010, 15 cities in Xinjiang emitted a total of 304.06 million tonnes CO2, and 97.7% of those emissions were related to fossil fuel combustion (i.e. energy-related emissions), with the remaining 2.3% from industrial processes associated with the production of cement (i.e. process-related emissions). The consumption of raw coal and crude oil were the main sources of Xinjiang's emissions (50.3% and 23.0%, respectively), whereas ‘petroleum processing and coking’ and ‘power and heat production’ were the two sectors that contributed the largest emissions at 32.6% and 27.9%, respectively. The cities in Xinjiang presented considerable variations in the total CO2 emissions and emissions per capita. The emissions intensity and emissions per capita shared similar distributions, and the emissions are significantly spatial autocorrelated. Cities whose economies relied on emission-intensive pillar industries and/or energy mainly sourced from raw coal tended to have high emissions per capita and high emissions intensities. Those cities included Altay, Changji, Hami and Shihezi. We also examined the time-series emissions of Urumqi, the largest city, from 2005 to 2015. Urumqi presented a generally rising trend in CO2 emissions over the decade, with emissions increasing by 324.2%. The major driving sector was ‘power and heat’, which showed increases in the total CO2 emissions and percentage of Xinjiang's emissions. Based on the findings, policy recommendations for emission reductions and low-carbon development for the cities in Xinjiang are provided, including adjusting the energy structure and introducing multiple industries.

The implementation of CO2 emission mitigation policies in cities is the key to China achieving its national emission mitigation targets. China is experiencing rapid urbanization and facing huge inequality in regional development and then shrinking cities generate. This study, for the first time, discusses long-term CO2 emission patterns of shrinking cities with comparisons of growing cities. 55 cities in Northeast China and the Yangtze River Delta are selected as cases. We first categorize these cities into three groups of shrinking cities and three groups of growing cities with a population index. Each group’s emission patterns in terms of energy, employment and industry structures are then examined. We find that CO2 emissions in the rapidly shrinking group presented a continuously increasing trend, while the other five groups reached their emission peaks in 2011–2013. For slightly and moderately shrinking groups, CO2 emission mitigation was a positive sign but occurred with the decline of secondary industry, especially for resource-based or heavy manufacturing cities, such as Daqing and Anshan in Northeast China. In the case of three types of growing cities, cities were capable of mitigating CO2 emissions and maintaining economic growth. The slightly growing group was the optimal type among these six groups. Its CO2 emissions experienced a decline with an annual rate of −1.47% during 2013–2015, while the economy still soared (increased by 7.27% annually). New economic growth points should be fostered to mitigate further shrinkage and achieve sustainable development for shrinking cities. The cities’ categorization rules, research thinking, and results offered in this study could provide a reference for other cities or developing countries at similar industrialization/urbanization phases to abbreviate their path towards a low-carbon economy.

Motivated by the Sustainable Development Goals (SDGs) and its impact by 2030, this study examines the relationship between energy consumption (SDG 7), climate (SDG 13), economic growth and population in Kenya, Senegal and Eswatini. We employ a Kernel Regularized Least Squares (KRLS) machine learning technique and econometric methods such as Dynamic Ordinary Least Squares (DOLS), Fully Modified Ordinary Least Squares (FMOLS) regression, the Mean-Group (MG) and Pooled Mean-Group (PMG) estimation models. The econometric techniques confirm the Environmental Kuznets Curve (EKC) hypothesis between income level and CO2 emissions while the machine learning method confirms the scale effect hypothesis. We find that while CO2 emissions, population and income level spur energy demand and utilization, economic development is driven by energy use and population dynamics. This demonstrates that income, population growth, energy and CO2 emissions are inseparable, but require a collective participative decision in the achievement of the SDGs.

Non-flow periods in fluvial ecosystems are a global phenomenon. Streambed drying and rewetting by sporadic rainfalls could drive considerable changes in the microbial communities that govern stream nitrogen (N) availability at different temporal and spatial scales. We performed a microcosm-based experiment to investigate how dry period duration (DPD) (0, 3, 6, and 9 weeks) and magnitude of sporadic rewetting by rainfall (0, 4, and 21 mm applied at end of dry period) affected stocks of N in riverbed sediments, ammonia-oxidizing bacteria (AOB) and archaea (AOA) and rates of ammonia oxidation (AO), and emissions of nitrous oxide (N2O) to the atmosphere. While ammonium (NH4+) pool size decreased, nitrate (NO3-) pool size increased in sediments with progressive drying. Concomitantly, the relative and absolute abundance of AOB and, especially, AOA (assessed by 16S rRNA gene sequencing and quantitative PCR of ammonia monooxygenase genes) increased, despite an apparent decrease of AO rates with drying. An increase of N2O emissions occurred at early drying before substantially dropping until the end of the experiment. Strong rainfall of 21 mm increased AO rates and NH4+ in sediments, whereas modest rainfall of 4 mm triggered a notable increase of N2O fluxes. Interestingly, such responses were detected only after 6 and 9 weeks of drying. Our results demonstrate that progressive drying drives considerable changes in in-stream N cycling and the associated nitrifying microbial communities, and that sporadic rainfall can modulate these effects. Our findings are particularly relevant for N processing and transport in rivers with alternating dry and wet phases - a hydrological scenario expected to become more important in the future. MA was funded by a postdoctoral grant from IGB and from the Alexander von Humboldt Foundation. DS was additionally funded by MINECO through the project DIVERSION (CGL2016-77487-R) and by the Basque Government through a grant for Research Groups of the Basque University System (IT-951-16). MB was funded by the DFG project LakeMix (BE 6194/1-1). TU acknowledges financial support from ESF and Ministry of Education, Science and Culture of Mecklenburg-Western Pomerania project WETSCAPES (ESF/14-BM-A55-0032/16).

Tropical peatlands are one of the most important terrestrial ecosystems in terms of impact on the atmospheric greenhouse gas composition. Currently, greenhouse gas emissions from tropical peatlands following disturbances due to deforestation, drainage or wildfire are substantial. We quantified in situ nitrous oxide (N2O) fluxes during both dry and wet seasons using a closed chamber method at sites that represented differing land uses and land use change intensities in Central Kalimantan, Indonesia. Cumulative N2O fluxes were compared with carbon dioxide (CO2) and methane (CH4) fluxes. The mean N2O flux rates (N2O-N &plusmn: SD, mg m−2 h−1) varied as follows: drained forest (0.112 ± 0.293) > agricultural peat at the Kalampangan site (0.012 ± 0.026) > drained burned peat (0.011 ± 0.018) > agricultural peat at the Marang site (0.0072 ± 0.028) > undrained forest (0.0025 ± 0.053) > clear-felled, drained, recovering forest (0.0022 ± 0.021). The widest N2O flux range was detected in the drained forest (max. 2.312 and min. −0.043 mg N2O-N m−2 h−1). At the other flux monitoring sites the flux ranges remained at about one tenth that of the drained forest site. The highest N2O emission rates were observed at water tables close to the peat surface where also the flux range was widest. Annual cumulative peat surface N2O emissions (expressed in CO2 equivalents as a percentage of the total greenhouse gas (N2O, CO2 and CH4) emissions) were 9.2 % at highest, but typically ~1 %. Average N2O fluxes and also the total of monitored GHG emissions were highest in drainage-affected forest which is characterized by continuous labile nitrogen availability from vegetation, and water tables typically below the surface.

Swamp forests on deep tropical peatlands have undergone extensive deforestation and draining for agriculture and plantations, consequently becoming globally significant carbon (C) sources. To study the effects of land-use change on peat as a biological environment, which directly affects decomposition dynamics and greenhouse gas emissions, we sampled peat from four common land-use types representing different management intensities in Central Kalimantan, Indonesia. The near-pristine swamp forest was used to describe unmanaged conditions, and the three other sites in order of increasing management intensity were reforested; degraded; and agricultural. We examined peat substrate quality (total C & nitrogen (N), dissolved organic C (DOC) and N (DON)), organic matter quality characterized by infrared spectroscopy, and microbial biomass and extracellular enzyme activity, to describe both biotic and abiotic conditions in peat. We found that the peat at altered sites was poorer in quality, i.e. decomposability, as demonstrated by the higher intensity of aromatic and aliphatic compounds, and lower intensity of polysaccharides, and concentration of total N, DOC, and DON compared to the peat in the swamp forest. The observed differences in peat properties can be linked to changes in litter input and decomposition conditions altered after deforestation and draining, as well as increased leaching and fires. The quality of the peat substrate was directly related to its biotic properties, with altered sites generally having lower microbial biomass and enzyme activity. However, irrespective of management intensity or substrate quality, enzyme activity was limited primarily to the first 0–3 cm of the peat profile. Some differences between wet and dry seasons were observed in enzyme activity especially in swamp forest, where the most measured enzyme activities were higher in dry season. Reforestation 6 years before our measurements had not yet restored enzyme activity in the peat to the level of the swamp forest, although the topmost peat characteristics in the reforested site already resembled those in the swamp forest. This is likely contributed by the limited capacity of the young tree stand to produce litter to support peat formation and restore the quality and structure of the peat, and the chemical weed control performed at the site. Therefore, we conclude that intensive land management, including deforestation and draining, leads to the surface peat becoming poorer biological environment, and it may take long time to restore the peat properties.

The main goal of the Paris Agreement as stated in Article 2 is ‘holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C’. Article 4 points to this long-term goal and the need to achieve ‘balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases'. This statement on ‘greenhouse gas balance’ is subject to interpretation, and clarifications are needed to make it operational for national and international climate policies. We study possible interpretations from a scientific perspective and analyse their climatic implications. We clarify how the implications for individual gases depend on the metrics used to relate them. We show that the way in which balance is interpreted, achieved and maintained influences temperature outcomes. Achieving and maintaining net-zero CO 2 -equivalent emissions conventionally calculated using GWP 100 (100-year global warming potential) and including substantial positive contributions from short-lived climate-forcing agents such as methane would result in a sustained decline in global temperature. A modified approach to the use of GWP 100 (that equates constant emissions of short-lived climate forcers with zero sustained emission of CO 2 ) results in global temperatures remaining approximately constant once net-zero CO 2 -equivalent emissions are achieved and maintained. Our paper provides policymakers with an overview of issues and choices that are important to determine which approach is most appropriate in the context of the Paris Agreement. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

International audience; Perennial rivers and streams make a disproportionate contribution to global carbon (C) cycling. However, the contribution of intermittent rivers and ephemeral streams (IRES), which sometimes cease to flow and can dry completely, is largely ignored although they represent over half the global river network. Substantial amounts of terrestrial plant litter (TPL) accumulate in dry riverbeds and, upon rewetting, this material can undergo rapid microbial processing. We present the results of a global research collaboration that collected and analysed TPL from 212 dry riverbeds across major environmental gradients and climate zones. We assessed litter decomposability by quantifying the litter carbon-to-nitrogen ratio and oxygen (O2) consumption in standardized assays and estimated the potential short-term CO2 emissions during rewetting events. Aridity, cover of riparian vegetation, channel width and dry-phase duration explained most variability in the quantity and decomposability of plant litter in IRES. Our estimates indicate that a single pulse of CO2 emission upon litter rewetting contributes up to 10% of the daily CO2 emission from perennial rivers and stream, particularly in temperate climates. This indicates that the contributions of IRES should be included in global C-cycling assessments.

Livestock manure contributes considerably to global emissions of ammonia (NH3 ) and greenhouse gases (GHG), especially methane (CH4 ) and nitrous oxide (N2 O). Various measures have been developed to mitigate these emissions, but most of these focus on one specific gas and/or emission source. Here, we present a meta-analysis and integrated assessment of the effects of mitigation measures on NH3 , CH4 and (direct and indirect) N2 O emissions from the whole manure management chain. We analysed the effects of mitigation technologies on NH3 , CH4 and N2 O emissions from individual sources statistically using results of 126 published studies. Whole-chain effects on NH3 and GHG emissions were assessed through scenario analysis. Significant NH3 reduction efficiencies were observed for (i) housing via lowering the dietary crude protein (CP) content (24-65%, compared to the reference situation), for (ii) external slurry storages via acidification (83%) and covers of straw (78%) or artificial films (98%), for (iii) solid manure storages via compaction and covering (61%, compared to composting), and for (iv) manure application through band spreading (55%, compared to surface application), incorporation (70%) and injection (80%). Acidification decreased CH4 emissions from stored slurry by 87%. Significant increases in N2 O emissions were found for straw-covered slurry storages (by two orders of magnitude) and manure injection (by 26-199%). These side-effects of straw covers and slurry injection on N2 O emission were relatively small when considering the total GHG emissions from the manure chain. Lowering the CP content of feed and acidifying slurry are strategies that consistently reduce NH3 and GHG emissions in the whole chain. Other strategies may reduce emissions of a specific gas or emissions source, by which there is a risk of unwanted trade-offs in the manure management chain. Proper farm-scale combinations of mitigation measures are important to minimize impacts of livestock production on global emissions of NH3 and GHG.

We investigated how the initial age structure of a managed, middle boreal (62°N), Norway spruce-dominated (Picea abies L. Karst.) forest area affects the net climate impact of using forest biomass for energy. The model-based analysis used a gap-type forest ecosystem model linked to a life cycle assessment (LCA) tool. The net climate impact of energy biomass refers to the difference in annual net CO2 exchange between the biosystem using forest biomass (logging residues from final felling) and the fossil (reference) system using coal. In the simulations over the 80-year period, the alternative initial age structures of the forest areas were (i) skewed to the right (dominated by young stands), (ii) normally distributed (dominated by middle-aged stands), (iii) skewed to the left (dominated by mature stands), and (iv) evenly distributed (same share of different age classes). The effects of management on net climate impacts were studied using current recommendations as a baseline with a fixed rotation period of 80 years. In alternative management scenarios, the volume of the growing stock was maintained 20% higher over the rotation compared to the baseline, and/or nitrogen fertilization was used to enhance carbon sequestration. According to the results, the initial age structure of the forest area affected largely the net climate impact of using energy biomass over time. An initially right-skewed age structure produced the highest climate benefits over the 80-year simulation period, in contrast to the left-skewed age structure. Furthermore, management that enhanced carbon sequestration increased the potential of energy biomass to replace coal, reducing CO2 emissions and enhancing climate change mitigation., final draft, peerReviewed

By exploiting data from the Toxic Release Inventory of the United States, we have established that the toxicological footprint (TF) increased by 3.3% (88.4 Mt) between 1998 and 1999 and decreased by 39% (1088.5 Mt) between 1999 and 2013. From 1999 to 2006, the decreasing TF was driven by improvements in emissions intensity (i.e. gains in production efficiency) through toxic chemical management options: cleaner production; end of pipe treatment; transfer for further waste management; and production scale. In particular, the mining sector reduced its TF through outsourcing processes. Between 2006 and 2009, decreasing TF was due to decrease in consumption volume triggered by economic recession. Since 2009, the economic recovery increased TF, overwhelming the influence of improved emissions intensity through population growth, consumption and production structures. Accordingly, attaining a less-toxic economy and environment will be influenced by a combination of gains in production efficiency through improvement in emissions mitigation technologies and changes in consumption patterns. Overall, the current analysis highlights the structural dynamics of toxic chemical release and would inform future formulation of effective mitigation standards and management protocols towards the detoxification of the environment., Scientific Reports, 6, 39514; 2016

Ecological (eco) taxes are promising mechanisms to enable eco-friendly decisions, but few people prefer them. In this study, we present a way in which eco-tax options may be communicated to general public to encourage their payment. Our implementation (called “information presentation”) takes advantage of the non-linear relationship between eco-tax payments and CO 2 emissions and the human reliance on the proportional-thinking heuristic. According to the proportional-thinking heuristic, people are likely to prefer a small eco-tax increase and judge larger eco-tax increases to cause proportionally greater CO 2 emissions reductions. In an online study, participants were asked to choose between eco-tax increases in two problems: In one, a smaller eco-tax increase resulted in greater CO 2 emissions reduction, while in the other, a smaller tax increase resulted in lesser CO 2 emissions reduction. Although the larger eco-tax increase did not reduce CO 2 emissions the most, across both problems, people judged larger eco-tax increases to cause proportionally greater reductions in CO 2 emissions and preferred smaller tax increases. Thus, eco-tax policies would benefit by presenting information in terms of eco-tax increases, such that smaller eco-tax increases (which are more attractive and are likely to be chosen by people) cause greater CO 2 emissions reductions.

International trade has become the fastest growing driver of global carbon emissions, with large quantities of emissions embodied in exports from emerging economies. International trade with emerging economies poses a dilemma for climate and trade policy: to the extent emerging markets have comparative advantages in manufacturing, such trade is economically efficient and desirable. However, if carbon-intensive manufacturing in emerging countries such as China entails drastically more CO 2 emissions than making the same product elsewhere, then trade increases global CO 2 emissions. Here we show that the emissions embodied in Chinese exports, which are larger than the annual emissions of Japan or Germany, are primarily the result of China's coal-based energy mix and the very high emissions intensity (emission per unit of economic value) in a few provinces and industry sectors. Exports from these provinces and sectors therefore represent targeted opportunities to address the climate-trade dilemma by either improving production technologies and decarbonizing the underlying energy systems or else reducing trade volumes.

Natural resource scarcity is no longer merely a remote possibility and governments increasingly seek information about the global distribution of resource use and related environmental pressures. This paper presents an international distributional analysis of natural resource use indicators. These encompass both territorial (national production) and footprint (national consumption) indicators for land-related pressures (human appropriation of net primary production, HANPP, and embodied HANPP), for material use (domestic material extraction and consumption and material footprint), and for carbon emissions (territorial carbon emissions and carbon footprints). Our main question is "What, both from a territorial and a footprint perspective, are the main driving factors of international environmental inequality?". We show that, for the environmental indicators we studied, inequality tends to be higher for footprint indicators than for territorial ones. The exception is land use intensity (as measured by HANPP), for which geographical drivers mainly determine the distribution pattern. The international distribution of material consumption is mainly a result of economic drivers whereas, for domestic extraction, demographic drivers can explain almost half of the distribution pattern. Finally, carbon emissions are the environmental pressure that shows the highest international inequality because of the larger contribution of economic drivers. (C) 2015 Elsevier Ltd. All rights reserved. Spanish research project [ECO2013-45380-P] Austrian National Science Fund FWF [P20812-G11, P21012-G11] FP7 project VOLANTE [265104] Economic and Social Research Council [ES/K006576/1]

The current development of tourism is environmentally unsustainable. Specifically, tourism's contribution to climate change is increasing while other sectors are reducing their greenhouse gas emissions. This paper has two goals: reveal the main structural cause for tourism's emission growth and show the consequences thereof for (mitigation) policies. It is reasoned that the main cause for tourism's strong emission growth is the time-space expansion of global tourism behavior. Contemporary tourism theory and geography fail to clearly describe this geographical development, making it difficult to understand this expansion and develop effective policies to mitigate environmental impacts. Therefore, this paper explores some elements of a 'new tourism geography' and shows how this may help to better understand the causes of the environmentally unsustainable development of tourism with respect to climate change and devise mitigation policies.