Co-control of carbon dioxide and air pollutant emissions in China from a cost-effective perspective

With increases in the economy and standards of living, energy consumption has grown significantly in China, which has resulted in serious local air pollution and greenhouse gas emissions. Because both carbon dioxide (CO₂) and air pollutant emissions mainly stem from fossil energy use, a co-control strategy is simulated and compared with single control in China, using an integrated assessment model (Global Change Assessment Model-Tsinghua University (GCAM-TU)) in this paper. We find that end-of-pipe (EOP) control measures play an important role in reducing air pollution in the near future, but in the long run, optimizing the energy system is an effective way to control both emissions. Reducing air pollutant might take a “free-ride” of decarbonizing the energy system. Compared with a single control of air pollutants, a co-control strategy is likely to reduce the requirement of EOP control measures. The result guides the Chinese government to consider a systemic and scientific plan for decarbonizing the energy system and co-controlling CO₂ and air pollutant, in order to avoid duplicate investments in infrastructure and lockup effect. The solution could be extended to many other developing countries, such as India and Africa, which is helpful to realize the goals of United Nations (UN) Sustainable Development Agenda.

     

Assessing negative carbon dioxide emissions from the perspective of a national “fair share” of the remaining global carbon budget

We present an assessment of the plausible Paris-aligned fair share nett cumulative carbon dioxide (CO₂) quota for an example nation state, the Republic of Ireland. By Paris-aligned, we mean consistent with the Paris Agreement adopted at the 21st Conference of the Parties to the United Nations Framework Convention on Climate Change, at Paris, France, in December 2015 (UNFCCC 2015). We compare and contrast this quota with both the aspirations expressed in the current Irish National Policy Position and current national emission projections. The fair share quota is assessed as a maximum of c. 391 million tonnes of carbon dioxide (MtCO₂), equal to 83 tonnes of carbon dioxide (tCO₂) per capita, from 2015, based on a precautionary estimate of the global carbon budget (GCB) and specific interpretation of global equity. Given Ireland’s high current CO₂ per capita emission rate, this would correspond to sustained year-on-year reductions in nett annual CO₂ emissions of over ??11% per year (beginning as of 2016). By contrast, the CO₂ mitigation target indicated in the National Policy Position corresponds to nett annual reduction rates in the range of only ?4.7% per year (low ambition) up to a maximum of ??8.3% per year (high ambition), and projections based on current and immediately planned mitigation measures indicate the possibility, instead, of sustained increases in emissions at a rate of the order of +?0.7% per year. Accordingly, there is a large gap between Paris-aligned ambition and current political and policy reality on the ground, with a significant risk of early emergence of “CO₂ debt” and tacit reliance on rapid deployment of currently speculative (at a relevant scale and feasible cost) negative CO₂ emission technologies to actively remove CO₂ from the atmosphere. While the detailed policy situation will clearly differ from country to country, we suggest that this methodology, and its CO₂debt framing, may be usefully applied in other individual countries or regions. We recommend that such framing be incorporated explicitly into a global mitigation strategy via the statements of nationally determined contributions required to be submitted and updated by all parties under the Paris Agreement processes.

     

High fluxes but different patterns of nitrous oxide and carbon dioxide emissions from soil in a cattle overwintering area

Cattle overwintering areas common in central Europe may represent significant point sources of the important greenhouse gases, nitrous oxide (N₂O) and carbon dioxide (CO₂). A 2-year field study was carried out in order to estimate the emissions of N₂O and CO₂ from soil in a cattle overwintering area located in the southwest of the Czech Republic. The measurements were performed at three sampling locations along a gradient of animal impact (severe, moderate, slight) to test the hypothesis that emissions of CO₂ and N₂O are positively related to the degree of impact. In addition to CO₂ and N₂O fluxes determined by using non-vented manual closed chambers, soil mineral nitrogen (NH₄⁺ and NO₃⁻), pH and temperature were determined to assess their regulatory role and impact on gas fluxes. The overwintering area was about 4 ha and it had been used for overwintering of about 90 cows since 1995. Deposition of animal excreta resulted in a significant accumulation of nitrogen in the soil during winter, but most of the N₂O was emitted during a few short periods in spring and/or in late autumn. Maximum N₂O fluxes of up to 2.5 mg N₂O-N m⁻² h⁻¹ were recorded at the most impacted location near the animal house, where the highest concentrations of soil mineral nitrogen also occurred. The emissions of CO₂ showed a completely different pattern to those of N₂O, being correlated with soil temperature; the highest emissions thus occurred in June–July, while very low fluxes were found in winter. Emission values ranged from about 0 to 700 mg C-CO₂ m⁻² h⁻¹. Furthermore, the effect of animal impact on CO₂ emissions was opposite to that on N₂O fluxes, as the highest CO₂ fluxes were mostly recorded at the least impacted location, where respiration of plants most likely increased overall CO₂ production. The results show that cattle overwintering areas are important sources of greenhouse gases, including N₂O and CO₂. Fluxes of these two gases are, however, differently distributed over the year, which also suggests that they are controlled by different environmental and soil factors.     

A comparison of five high-resolution spatially-explicit,fossil-fuel,carbon dioxide emission inventories for the United States

The quantification of fossil-fuel-related emissions of carbon dioxide to the atmosphere is necessary in order to accurately represent carbon cycle fluxes and to understand and project the details of the global carbon cycle. In addition, the monitoring, reporting, and verification (MRV) of carbon dioxide emissions is necessary for the success of international agreements to reduce emissions. However, existing fossil-fuel carbon dioxide (FFCO₂) emissions inventories vary in terms of the data and methods used to estimate and distribute FFCO₂. This paper compares how the approaches used to create spatially explicit FFCO₂ emissions inventories affect the spatial distribution of emissions estimates and the magnitude of emissions estimates in specific locales. Five spatially explicit FFCO₂ emission inventories were compared: Carbon Dioxide Information and Analysis Center (CDIAC), Emission Database for Global Atmospheric Research (EDGAR), Fossil Fuel Data Assimilation System (FFDAS), Open-source Data Inventory for Anthropogenic CO₂ (ODIAC), and Vulcan. The effects of using specific data and approaches in the creation of spatially explicit FFCO₂ emissions inventories, and the effect of resolution on data representation are analyzed using graphical, numerical, and cartographic approaches. We examined the effect of using top-down versus bottom-up approaches, nightlights versus population proxies, and the inclusion of large point sources. The results indicate that the approach used to distribute emissions in space creates distinct patterns in the distribution of emissions estimates and hence in the estimates of emissions in specific locations. The different datasets serve different purposes but collectively show the key role of large point sources and urban centers and the strong relationship between scale and uncertainty.     

Implications of uncertainty and scale in carbon emission estimates on locally appropriate designs to reduce emissions from deforestation and degradation (REDD+)

This study combined uncertainty analysis of carbon emissions with local stakeholders' perspectives to develop an effective Reducing Emission from Deforestation and Degradation (REDD+) scheme at the district level. Uncertainty of carbon emission estimates depends on scale while local stakeholders' views on plausible REDD+ schemes influence and limit transaction costs. The uncertainty analysis formed the basis for determining an appropriate scale for monitoring carbon emission estimates as performance measures for REDD+ incentives. Our analysis of stakeholder’ perspectives explored (i) potential location and activities for lower emission development pathways, and (ii) perceived fair allocation of REDD+incentives. Our case study focused on frontier forest in Tanjung Jabung Barat District, Jambi, Indonesia. The uncertainty analysis used Monte Carlo simulation techniques using known inaccuracy of land cover classification and variation in carbon stocks assessment per land cover type. With decreasing spatial resolution of carbon emission maps, uncertainty in carbon estimates decreased. At 1 km² resolution uncertainty dropped below 5 %, retaining most of the coarser spatial variation in the district. Fairness, efficiency and transaction cost issues in the design of REDD+ mechanisms were readily recognized by local stakeholders, who converged on an equal allocation to short-term efficiency (emission reduction activities) and long-term fairness (alternative livelihood development). A striking difference occurred in desirable transaction costs (which include monitoring, reporting and verification), with Non-Governmental Organizations (NGOs) aiming for 8 %, while government and researchers accepted transaction costs of 40 %. Feasible measures for emission reduction in the district, derived from a participatory planning process, are compatible with the 1 km² spatial resolution of performance measures.     

Quantifying energy use, carbon dioxide emission, and other environmental loads from island tourism based on a life cycle assessment approach

The main purpose of industrial ecology is to evaluate and minimize impacts from economic activities of human society. Tourism as one economic activity, results in a full range of environmental impacts, but few applications of industrial ecology to tourism management have previously been discussed. Life cycle assessment (LCA) is used in this research to explore environmental impacts of island tourism, and then the environmental loads per tourist per trip can be found. Penghu Island in Taiwan is taken as an example to examine this new approach. Various environmental loads in transportation, accommodation, and recreation activity sector are all inventoried and calculated here. In summary, per tourist per trip uses 1606 MJ of energy, 607 L of water, and emits 109,034 g of CO₂, 2660 g of CO, 597 g of HC, 70 g of NO_x. In addition, per tourist per trip also discharges 416 L of wastewater, 83.1 g of BOD, and 1.95 g of solid waste. In terms of energy use, the transportation consumes the largest energy (67%); in particular, the airplane sector. Moreover, per Penghu tourist results in more environmental loads than local people; for example, the amount of solid waste discharge per tourist is 1.95 kg per day, while that of per local people is 1.18 kg. Finally, the advantages and limitations of such LCA approach are also discussed.     

Can integrated control strategies for multiple emissions enhance cost-efficiency in environmental policy?: Evidence from Sweden

The aim of this paper is to clarify the magnitude of the sub-optimization cost associated with separate control strategies for compliance with the Swedish environmental quality objectives. The marginal reduction costs are estimated using a separate and an integrated version of a deterministic linear programming model. To investigate whether the accuracy of the data is decisive for the result of this study, an extensive sensitivity analysis that deals with both the disparity in discount rates in data and the different types of measures, is carried out in four steps. It can be concluded that the results are robust for possible and probable faults in data. The main findings are that there are no substantial sub-optimization costs for separate control strategies for CO₂, NO_X and SO₂, but an integrated action strategy could imply enhanced cost-efficiency in reductions of VOC and particles.     

The sensitivity of the costs of reducing emissions from deforestation and degradation (REDD) to future socioeconomic drivers and its implications for mitigation policy design

Mitigation and Adaptation Strategies for Global Change - Climate change mitigation policies for the land use, land use change, and forestry (LULUCF) sector are commonly assessed based on marginal...     

A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling

Mitigation and Adaptation Strategies for Global Change - Industrial processes cause significant emissions of greenhouse gases (GHGs) to the atmosphere and, therefore, have high mitigation and...     

Mitigation potential of important farm and forest trees: a potentiality for clean development mechanism afforestation reforestation (CDM A R) project and reducing emissions from deforestation and degradation,along with conservation and enhancement of carbon stocks (REDD+)

The effectiveness and integrity of forest-based emissions reduction schemes such as Clean Development Mechanism Afforestation Reforestation (CDM A R) project and Reducing Emissions from Deforestation and Degradation (REDD+), along with conservation and enhancement of carbon (C) stocks implementation and assessment in developing countries are required not only, the appropriate monitoring and evaluation, rather the precise values of constants being used to estimate the C stocks or C credit in place of default or guess value. Estimates are reported of the C content of wood of four forest species (Shorea robusta, Pinus roxburghii, Tectona grandis and Cinnamomum camphora) and two important farm species (Populus deltoides and Eucalyptus treticornis) in the temperate region of Indian Himalayas, derived using the ash content method. These species were considered keeping in view of their potentiality for the C sequestration and storage projects across the developing countries specifically the South East Asian Countries. The specific gravity, ash content and C proportion is estimated for these six species by selecting random woods pieces. These estimates are designed to improve the calculations of biomass C for use in estimation of C credits in the developing region under CDM A R projects and REDD+ program supported by developed country. Regression analysis of C prediction models revealed that, for all six species, C content may be estimated through specific gravity of the wood by a linear equation without intercept. Indirectly, this results also implies that among the two farm trees, eucalyptus has high potentiality for C capturing and among four forest trees, Shorea robusta has high potentiality, therefore these two should have preference for plantation/regeneration as well as for conservation.