Greenhouse Gas Emission Inventories Research Articles

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

Industrial processes cause significant emissions of greenhouse gases (GHGs) to the atmosphere and, therefore, have high mitigation and adaptation potential for global change. Spatially explicit (gridded) emission inventories (EIs) should allow us to analyse sectoral emission patterns to estimate the potential impacts of emission policies and support decisions on reducing emissions. However, such EIs are often based on simple downscaling of national level emission estimates and the changes in subnational emission distributions do not necessarily reflect the actual changes driven by the local emission drivers. This article presents a high-definition, 100-m resolution bottom-up inventory of GHG emissions from industrial processes (fuel combustion activities in energy and manufacturing industries, fugitive emissions, mineral products, chemical industries, metal production and food and drink industries), which is exemplified for data for Poland. The study objectives include elaboration of the universal approach for mapping emission sources, algorithms for emission disaggregation, estimation of emissions at the source level and uncertainty analysis. We start with IPCC-compliant national sectoral GHG estimates made using Polish official statistics and, then, propose an improved emission disaggregation algorithm that fully utilises a collection of activity data available at the national/provincial level to the level of individual point and diffused (area) emission sources. To ensure the accuracy of the resulting 100-m resolution emission fields, the geospatial data used for mapping emission sources (point source geolocation and land cover classification) were subject to thorough human visual inspection. The resulting 100-m emission field even holds cadastres of emissions separately for each industrial emission category. We also compiled cadastres in regular grids and, then, compared them with the Emission Database for Global Atmospheric Research (EDGAR). A quantitative analysis of discrepancies between both results reveals quite frequent misallocations of point sources used in the EDGAR compilation that considerably deteriorate high-resolution inventories. We also use a Monte-Carlo method-based uncertainty assessment that yields a detailed estimation of the GHG emission uncertainty in the main categories of the analysed processes. We found that the above-mentioned geographical coordinates and patterns used for emission disaggregation have the greatest impact on the overall uncertainty of GHG inventories from the industrial processes. We evaluate the mitigation potential of industrial emissions and the impact of separate emission categories. This study proposes a method to accurately quantify industrial emissions at a policy relevant spatial scale in order to contribute to the local climate mitigation via emission quantification (local to national) and scientific assessment of the mitigation effort (national to global). Apart from the above, the results are also of importance for studies that confront bottom-up and top-down approaches and represent much more accurate data for global high-resolution inventories to compare with.

Options to feed plastic waste back into the manufacturing industry to achieve a circular carbon economy

Plastic waste disposal practices and subsequent leakage into the environment are creating environmental, economic, and social problems. Reduction of plastic waste generation is one of the main solutions offered to remedy the plastic waste problem. However, it is undeniable that plastics play a significant role in benefiting humanity. Plastic medical devices save lives, household equipment and vehicle components are lighter and more fuel efficient. Conventional plastics are produced from virgin fossil feedstocks (oil and natural gas), and their carbon footprint is contributing to the problem of climate change. However, greenhouse gas (GHG) emission inventories generally report that emissions related to global waste management may not be as high as other GHG sources, i.e. electricity generation from fossil fuel combustion or transportation, concluding that innovative approaches in the waste management sector may not substantially contribute to climate change mitigation efforts. This paper examines near or long term technical and policy changes needed that can support environmental health, mitigate climate change, and promote social justice by feeding plastic waste back into the circular carbon economy.

Decreasing Rice Cropping Intensity in Southern China from 1990 to 2015

Assessing changes in rice cropping systems is essential for ensuring food security, greenhouse gas emissions, and sustainable water management. However, due to the insufficient availability of images with moderate to high spatial resolution, caused by frequent cloud cover and coarse temporal resolution, high-resolution maps of rice cropping systems at a large scale are relatively limited, especially in tropical and subtropical regions. This study combined the difference of Normalized Difference Vegetation Index (dNDVI) method and the Normalized Difference Vegetation Index (NDVI) threshold method to monitor changes in rice cropping systems of Southern China using Landsat images, based on the phenological differences between different rice cropping systems. From 1990–2015, the sown area of double cropping rice (DCR) in Southern China decreased by 61054.5 km2, the sown area of single cropping rice (SCR) increased by 20,110.7 km2, the index of multiple cropping decreased from 148.3% to 129.3%, and the proportion of DCR decreased by 20%. The rice cropping systems in Southern China showed a “double rice shrinking and single rice expanding” change pattern from north to south, and the most dramatic changes occurred in the Middle-Lower Yangtze Plain. This study provided an efficient strategy that can be applied to moderate to high resolution images with deficient data availability, and the resulting maps can be used as data support to adjust agricultural structures, formulate food security strategies, and compile a greenhouse gas emission inventory.

Sectoral performance analysis of national greenhouse gas emission inventories by means of neural networks

Annual greenhouse gas emissions have increased more than threefold between 1950 and 2014, posing a major threat to the integrity of the entire earth system and subsequently to humankind. Consequently, roadmaps towards low-carbon pathways are urgently needed. Our study contributes to a more detailed understanding of the dynamics of country based emission patterns and uses them to discuss prospective low-carbon pathways for countries. As availability of databases on sectoral emissions substantially increased, we employ machine learning techniques to classify emission features and pathways. By doing so, 18 representative emission patterns are derived. Overall emissions from seven sectors and for 167 countries covering the time span from 1950 to 2014 have been used in the analyses. The following significant trends can be observed: a) increasing per capita emissions due to growing fossil fuel use in many parts of the world, b) a decline in per capita emissions in some countries, and c) a shift in the emission shares, i.e., a reduction of agricultural and land use contributions in certain regions. Using the emission patterns, their dynamics, and best performing countries as role models, we show the possibility for gaining a decent human development without significantly increasing per capita emissions.

How much CO2 is stored and verified through CCS/CCUS in China?

Verifying the amount of CO2 geological storage is the key to evaluating CO2 emission reduction effect of CCUS projects. This paper based on the examples in China, according to the characteristics of different CO2-EOR projects, proposes a methodology for evaluating the amount of CO2 geological storage. The key of the method is evaluating CCUS chain from capture, transportation, EOR with storage, and finance. The evidence from different steps of CCUS must confirm each other so that it helps us to determine the amount of CO2 storage in case of missing some evidence. Further, based on this method, this paper evaluates the actual CO2-EOR with geological storage project in China. The method proposed in this paper will not only help third parties compile enterprise greenhouse gas emission reports and inventories, but also helps government to subsidize CO2 emission reduction enterprises. It will be useful for industries that implementing CCUS projects to provide key evaluation parameters and carry out necessary monitoring technologies.

Urban Mobility and Greenhouse Gas Emissions: Status, Public Policies, and Scenarios in a Developing Economy City, Natal, Brazil

This study aims to deepen the understanding of the role of the urban mobility sector in the current and future greenhouse gas (GHG) emissions of a middle-sized city of Brazil, which is also a developing economy. With the cross-reference between road and rail mobility data, governmental mobility planning, the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC) of the Intergovernmental Panel on Climate Change (IPCC) emission quantification methodology, and the creation of scenarios for up to 10 subsequent years, it is possible to verify that individual motorized transport accounts for 60% of the total emissions from the urban transportation sector, with the largest amount of carbon dioxide equivalent (CO2eq) emissions per passenger among all of the forms of mobility. However, in the case of this study, government mobility planning, by not encouraging more energy-efficient transport and non-motorized modes, ends up aggravating GHG emissions in the scenarios considered for 2020 and 2025. In turn, the mitigation scenarios proposed herein integrate public transport and non-motorized transport solutions that would reduce the total of equivalent carbon dioxide (tCO2eq) by at least 45,000 tCO2eq per year by 2025. This cross-referencing of the environmental impact of government mobility policies can be replicated in other cities in developing countries that do not yet present municipal inventories or emission monitoring.

Carbon accounting framework for decarbonisation of European city neighbourhoods

Strategies for climate change mitigation in European cities have become more urgent and require actions to proactively involve administrators, citizens and other stakeholders and let them cooperate to accomplish widely approved plans for decarbonisation. Nevertheless, considering the short term of political mandates and the instability of social-economic-legal variables in our changing world, urban planning practices will require more effective and rapid decision support systems to easily access and process information. The paper presents an optimised carbon accounting methodology to assess greenhouse gas (GHG) emissions in specific urban environments and inform urban policies and design. In particular, this procedure, substantially inspired by the IPCC standard methodology for GHG emissions inventory of Nations, constitutes the framework of a “mediate model” with a dual role: to both assess the Carbon Footprint of urban neighbourhoods and to estimate the effects, in terms of Carbon Footprint mitigation, of action plans addressed to carbon neutrality. For demonstration, the carbon accounting framework has been performed based on average European values. The procedure started by profiling the typical household as functional unit, whose carbon footprint has been estimated 6.93 t CO2-eq/yr, referring to energy use for housing and mobility, domestic waste treatment and water use. The impact of the average European neighbourhood has been obtained by scaling up to 10,000 households (23,000 inhabitants) as benchmark for future applications. An additional outcome concerns the innovative spatial visualisation of results in terms of equivalent forestland (e.g. the emission of one average European household corresponds to the quantity of CO2 yearly absorbed by 0.51 ha of forest), that allows for understanding intensity and size of impacts in order to consistently support awareness raising initiatives targeting citizens and stakeholders and communication-dissemination activities.

Measuring methane emissions from abandoned and active oil and gas wells in West Virginia

Recent studies have reported methane (CH4) emissions from abandoned and active oil and gas infrastructure across the United States, where measured emissions show regional variability. To investigate similar phenomena in West Virginia, we measure and characterize emissions from abandoned and active conventional oil and gas wells. In addition, we reconcile divergent regional CH4 emissions estimates by comparing our West Virginia emissions estimates with those from other states in the United States. We find the CH4 emission factors from 112 plugged and 147 unplugged wells in West Virginia are 0.1 g CH4 h−1 and 3.2 g CH4 h−1, respectively. The highest emitting unplugged abandoned wells in WV are those most recently abandoned, with the mean emission of wells abandoned between 1993 and 2015 of 16 g CH4 h−1 compared to the mean of those abandoned before 1993 of 3 × 10−3 g CH4 h−1. Using field observations at a historic mining area as a proxy for state-wide drilling activity in the late 19th/early 20th century, we estimate the number of abandoned wells in WV at between 60,000 and 760,000 wells. Methane emission factors from active conventional wells were estimated at 138 g CH4 h−1. We did not find an emission pattern relating to age of wells or operator for active wells, however, the CH4 emission factor for active conventional wells was 7.5 times larger than the emission factor used by the EPA for conventional oil and gas wells. Our results suggest that well emission factors for active and abandoned wells can vary within the same geologic formation and may be affected by differences in state regulations. Therefore, accounting for state-level variations is critical for accuracy in greenhouse gas emissions inventories, which are used to guide emissions reduction strategies.

Transnational Municipal Climate Networks and the Politics of Standardisation: The Contested Role of Climate Data in the New Global Covenant of Mayors for Climate and Energy

This article analyses the formation of a new global network, the Global Covenant of Mayors for Climate & Energy (GCoM), by two existing initiatives, the EU-based Covenant of Mayors and the UN-supported Compact of Mayors. While this merger of two transnational networks provides evidence for the increased coordination and standardisation of transnational municipal climate action, this remains a contentious and incomplete process. The article identifies different modes of transnational climate governance that have contributed to conflict between the founding networks and zooms in on the role of municipal climate data. Using empirical evidence, it analyses the contested politics of municipal climate data, including the role of the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC) as a standard tool, the definition of a common target, and the inclusion of financial actors. Concerns over the reshaping of public-private boundaries and the possible commodification of public data are identified as major obstacles for the (EU) Covenant of Mayors, which consequentially seeks to remain as independent as possible within the new GCoM. Data politics emerges as a crucial factor for the future direction of transnational municipal climate policy and the ongoing processes of standardisation and coordination.

The crux with reducing emissions in the long-term: The underestimated \u201cnow\u201d versus the overestimated \u201cthen\u201d

The focus of this perspective piece is on memory, persistence, and explainable outreach of forced systems, with greenhouse gas (GHG) emissions into the atmosphere serving as our case in point. In the light of the continued increase in emissions globally vis-à-vis the reductions required without further delay until 2050 and beyond, we conjecture that, being ignorant of memory and persistence, we may underestimate the “inertia” with which global GHG emissions will continue on their increasing path beyond today, thus, also leading to the amount of reduction that can be achieved in the future being overestimated. This issue is at the heart of mitigation and adaptation. For a practitioner, this translates to the problem of how persistently an emissions system behaves when subjected to a specified mitigation measure and which emissions level to adapt to for precautionary reasons in the presence of uncertainty. Memory allows us to reference how strongly the past can influence the “near-term future” of the system or (what we define as) its explainable outreach. We consider memory to be an intrinsic property of a system, retrospective in nature; and persistence to be a consequential (i.e., observable) feature of memory, prospective in nature and reflecting the tendency of a system to preserve a current state (including trend). Persistence depends on the system’s memory which, in turn, reflects how many historical states directly influence the current one. The nature of this influence can range from purely deterministic to purely stochastic. Different approaches exist to capture memory. We capture memory generically with the help of three characteristics: its temporal extent and both its weight and quality over time. The extent of memory quantifies how many historical data directly influence the current data point. The weight of memory describes the strength of this influence (fading of memory), while the quality of memory steers how well we know the latter (blurring of memory). Capturing fading and blurring of memory in combination is novel. In a numerical experiment with the focus on systemic insight, we cast a glance far ahead by illustrating one way to capture memory, and to understand how persistence plays out and how an explainable outreach of the system can be derived even under unfavorable conditions. We look into the following two questions: (1) Do we learn properly from the past? That is, do we have the right science in place to understand and treat memory appropriately? And (2) being aware that memory links a system’s past with its near-term future, do we quantify this outreach in a way that is useful for prognostic modelers and decision-makers? The latter question implies another question, namely, whether we can differentiate between and specify the various characteristics of memory (i.e., those mentioned above) by way of diagnostic data-processing alone? Or, in other words, how much system understanding do we need to have and to inject into the data-analysis process to enable such differentiation? Although the prime intention of our perspective piece is to study memory, persistence, and explainable outreach of forced systems and, thus, to expand on the usefulness of GHG emission inventories, our insights indicate the high chance of our conjecture proving true: being ignorant of memory and persistence, we underestimate, probably considerably, the “inertia” with which global GHG emissions will continue on their historical path beyond today and thus overestimate the amount of reductions that we might achieve in the future.

Share of road transport in greenhouse gas emissions in Poland in 1988–2015

Abstract The results of an analysis of the greenhouse gas (GHG) emission inventory in Poland in the years 1988–2015 are presented, paying special attention to the impact of road transport on the intensification of greenhouse effect. The analysis was made based on the official results compiled by the National Centre for Emissions Management and Balancing (KOBiZE) at the Institute of Environmental Protection – National Research Institute. It was found that carbon dioxide emission represented the dominant part of the total GHG emissions, despite that there were other gases having far greater greenhouse effect potential. There was a general downward trend for the national annual emission of basic GHGs. The estimated share of road transport in the GHGs emission was not high: from 4% in 1988 to around 12% in 2015. For motor vehicles, there is a dominant share in the GHGs emissions of passenger cars: (50 ÷ 60)%. In the years 1988–2015, there was a relative decrease by about 32% in the national annual emission of carbon dioxide equivalent from all sources covered by the inventory. That notwithstanding, the national annual emission of carbon dioxide equivalent arising from transportation increased generally by about 93% and that from the road transport increased by as much as 117%. The increase in GHGs emissions from motor vehicles resulted mainly from a significant growth in car numbers. Technical progress in the construction of motor vehicles can be evaluated by considering the average annual emission of carbon dioxide equivalent from a conventional car, which has been decreasing since 1998.

Greenhouse gas emission from motor vehicles in Poland in 2015

Abstract The article presents the results of the inventory of greenhouse gas emissions from motor vehicles in Poland in 2015. The inventory was developed in accordance with the applicable guidelines for the annual greenhouse gas emission inventory (Decision 24/CP.19 of the Conference of the Parties to the United Nations Framework Convention on Climate Change) by the National Centre for Emissions Management and Balancing (KOBiZE) at the Institute of Environmental Protection – the National Research Institute. The national annual gas emissions from road transport are presented, including: carbon dioxide, methane and nitrous oxide along with emissions of the above gases converted into carbon dioxide equivalents. Carbon dioxide makes up the largest share in carbon dioxide emissions. This is particularly evident in the case of road transport – the emission of gases other than carbon dioxide (methane and nitrous oxide) is several orders of magnitude lower than the emission of carbon dioxide. Carbon dioxide emissions from road transport account currently for approximately 14% of the total carbon dioxide emission in Poland.

Estimating perfluorocarbon emission factors for industrial rare earth metal electrolysis

Rare earth (RE) metals have been widely applied in new materials, leading to their drastic production increase in the last three decades. In the production process featured by the molten-fluoride electrolysis technology, perfluorocarbon (PFC) emissions are significant and therefore deserve full accounting in greenhouse gas (GHG) emission inventories. Yet, in the ‘2006 IPCC Guidelines for National Greenhouse Gas Inventories’, no method currently exists to account for PFC emissions from rare earth metal production. This research aims to determine emission factors for industrial rare earth metals production through on-site monitoring and lab analysis of PFC concentrations in the exhaust gases from rare earth metal electrolysis. Continuous FTIR measurements and time-integrated samples (analysed off-site by high-precision Medusa GC–MS) were conducted over 24–60 h periods from three rare earth companies in China, covering production of multiple rare earth metals/alloys including Pr-Nd, La and Dy-Fe. The study confirmed that PFC emissions are generated during electrolysis, typically in the form of CF4 (∼90% wt of detected PFCs), C2F6 (∼10%) and C3F8 (<1%); trace levels of c-C4F8 and C4F10 were also detected. In general, PFC emission factors vary with rare earth metal produced and from one facility to another, ranging from 26.66 to 109.43 g/t-RE for CF4 emissions, 0.26 to 10.95 g/t-RE for C2F6, and 0.03 to 0.27 g/t-RE for C3F8. Converted to 211.60 to 847.41 kg CO2-e/t-RE for total PFCs, this emissions intensity for rare earths electrolysis is of lower (for most RE production) or similar (Dy-Fe production) level of magnitude to industrial aluminium electrolysis.

Inverse Estimation of an Annual Cycle of California's Nitrous Oxide Emissions

AbstractNitrous oxide (N2O) is a potent long‐lived greenhouse gas (GHG) and the strongest current emissions of global anthropogenic stratospheric ozone depletion weighted by its ozone depletion potential. In California, N2O is the third largest contributor to the state's anthropogenic GHG emission inventory, though no study has quantified its statewide annual emissions through top‐down inverse modeling. Here we present the first annual (2013–2014) statewide top‐down estimates of anthropogenic N2O emissions. Utilizing continuous N2O observations from six sites across California in a hierarchical Bayesian inversion, we estimate that annual anthropogenic emissions are 1.5–2.5 times (at 95% confidence) the state inventory (41 Gg N2O in 2014). Without mitigation, this estimate represents 4–7% of total GHG emissions assuming that other reported GHG emissions are reasonably correct. This suggests that control of N2O could be an important component in meeting California's emission reduction goals of 40% and 80% below 1990 levels of the total GHG emissions (in CO2equivalent) by 2030 and 2050, respectively. Our seasonality analysis suggests that emissions are similar across seasons within posterior uncertainties. Future work is needed to provide source attribution for subregions and further characterization of seasonal variability.

Engagement of scientific community and transparency in C accounting: the Brazilian case for anthropogenic greenhouse gas emissions from land use, land-use change and forestry

To effectively implement the Paris Agreement, capacity in carbon accounting must be strengthened in the developing world, and partnerships with local academic institutions can do the accounting for governments and fill the capacity gap. This paper highlights the Brazilian case, focusing on ways in which climate change science information and transparency are being incorporated in national C accounting initiatives, particularly the national inventory of greenhouse gas (GHG) emissions and removals. We report how the third inventory for the sector of land use, land-use change and forestry (LULUCF) was implemented to address scientific challenges involved in the monitoring of carbon stocks and land-use changes of diverse and complex biomes while addressing international and national policy demands (report and decision support) and transparency to various stakeholders. GHG emissions and removals associated with 2002–2010 carbon changes in aboveground, belowground biomass, necromass and soil carbon by land use and land cover changes were estimated for all Brazilian biomes, and for the Amazon estimates were also presented for the periods of 2002–2005 and 2005–2010. The inventory improved regional estimates for carbon stock and national emission factors with the support and engagement of the scientific community. Incorporation of local context is essential to reduce uncertainties and properly monitor efforts to contribute to GHG emission/reduction targets. To promote transparency and make information more accessible, the national inventory results were made available by the National Emissions Registry System (SIRENE). This system was built to support climate change policies as an important legal apparatus and by increasing access to emissions and land-use change data.

City Carbon Footprint Evaluation and Forecasting Case Study: Dan Sai Municipality

In this research, City Carbon Footprint (CCF) of Dan Sai municipality was evaluated according to the Global Protocol for Community-scale Greenhouse Gas Emission Inventories (GPC) guideline. Related activity data in 2015 were collected and analyzed which presented into 3 scopes (Scope1, 2, 3). As the results, the total CCF of Dan Sai Municipality is 8,528.04 tCO2eq which contributed from scope 1, scope 2 and scope 3 of 5,524 tCO2eq, 2,164 tCO2eq, 1,140 tCO2eq, respectively. Fossil fuel combustion from industrial sub-sector in scope 1 showed the greatest contribution of 40% of the total, followed by electricity consumption in scope 2, solid waste treatment in scope 1 accounting for 25% and 13%, respectively. The data of CCF in 2015 was used as baseline (Business as Usual: BAU) in order to predict city emissions in 2030 using mathematical forecasting model. The result indicated that CCF of Dan Sai can be reach up to 11,662.39 t CO2eq (27%). Consequently, applying mitigation options to reduce the emission for Dan Sai has been proposed. It was found that implementation of reduction projects including installation of solar rooftop, composting organic waste, producing RDF from waste and convert waste to energy by using RDF hybrid ORC could reduce CCF accounting for 20%, 0.53%, 1% and 3%, respectively. This study can provide benefits and offer better solutions for maximizing the potential of low carbon city and minimizing the climate change problem issues for municipality in the near future.

Carbon Footprint Planning: Quantifying Local and State Mitigation Opportunities for 700 California Cities

Consumption-based greenhouse gas (GHG) emissions inventories have emerged to describe full life cycle contributions of households to climate change at country, state and increasingly city scales. Using this approach, how much carbon footprint abatement potential is within the control of local governments, and which policies hold the most potential to reduce emissions? This study quantifies the potential of local policies and programs to meet aggressive GHG reduction targets using a consumption-based, high geospatial resolution planning model for the state of California. We find that roughly 35% of all carbon footprint abatement potential statewide is from activities at least partially within the control of local governments. The study shows large variation in the size and composition of carbon footprints and abatement opportunities by ~23,000 Census block groups (i.e., neighborhood-scale within cities), 717 cities and 58 counties across the state. These data and companion online tools can help cities better understand priorities to reduce GHGs from a comprehensive, consumption-based perspective, with potential application to the full United States and internationally.

Urban carbon dioxide equivalent (CO2e) accounting based on the GPC framework

PurposeThis paper aims to provide a typical example of accounting for the carbon dioxide equivalent (CO2e) in underdeveloped cities, especially for the Poyang Lake area in China. The accounting can increase public understanding and trust in climate mitigation strategies by showing more detailed data.Design/methodology/approachThe paper uses the “Global Protocol for Community-scale greenhouse gas emission inventories (GPC)” method, a worldwide comparable framework for calculating urban CO2e emission (CE). The empirical case is an underdeveloped city, Nanchang, in China.FindingsThe results show the total CE of Nanchang, containing the electricity CE of Scope 2, grew rapidly from 12.49 Mt in 1994 to 55.00 Mt in 2014, with the only recession caused by the global financial crisis in 2008. The biggest three contributors were industrial energy consumption, transportation and industrial processes, which contributed 44.71-72.06, 4.10-25.07 and 9.07-22.28 per cent, respectively, to the total CE. Almost always, more than 74.41 per cent of Nanchang’s CE was related to coal. When considering only the CEs from coal, oil and gas, these CEs per unit area of Nanchang were always greater than those of China and the world. Similarly, these CEs per gross domestic product of Nanchang were always bigger than those of the world. Thus, based on these conclusions, some specific countermeasures were recommended.Originality/valueThis paper argues that the CO2e accounting of underdeveloped cities by using the GPC framework should be promoted when designing climate mitigation policies. They can provide more scientific data to justify related countermeasures.

Environmental policies for GHG emissions reduction and energy transition in the medieval historic centre of Siena (Italy): the role of solar energy

Abstract The cities are playing a leading role in action to reduce the global CO2 emissions. In this paper a greenhouse gas (GHG) balance of the medieval historic centre of Siena (Tuscany, Italy) has been performed for the first time. It was compiled by a top down approach and according to the latest IPCC guidelines released in 2006. The results show a balance far from carbon neutrality and offer ideas for testing appropriate environmental policies based on improving energy efficiency (such as energy saving and integrated waste management) as well on transition towards renewable energies. The proposed strategies, and in particular the installation of photovoltaic panels on roofs, showed a substantial reduction in gross GHG emissions (−57%) in the short run (about 10 years) and enable carbon neutral status to be reached in the long run (about 30 years). Carbon status further improves when the electricity obtained from the photovoltaic panels is used for private/service sector needs (e.g. lights and electrical appliances), for public/household electric heating and for electric transport. Solar and other renewable resources represent the most desirable solution for decarbonisation but need specific concern in urban systems with a high degree of structural and historical constraints coherently with the scopes of the Global Protocol for Community-Scale GHG Emission Inventories (2014).

Life cycle greenhouse gas emissions of hydrogen fuel production from chlor-alkali processes in the United States

By-product hydrogen from chlor-alkali processes can help meet the increasing demand for hydrogen fuel in early fuel cell electric vehicle markets (e.g., California) in the U.S. Hydrogen produced from chlor-alkali plants is typically combusted for process heat on site, vented to the atmosphere (i.e., wasted), or sold to the external merchant hydrogen market. Whether it is combusted, vented, or sold as a commodity, relevant information is lacking as to the life-cycle environmental benefits or trade-offs of using by-product hydrogen from chlor-alkali plants. A life-cycle analysis framework was employed to evaluate well-to-gate greenhouse gas (GHG) emissions associated with by-product hydrogen from chlor-alkali processes in comparison with hydrogen from the conventional centralized natural gas steam methane reforming (central SMR) pathway. U.S.-specific, plant-by-plant, and up-to-date chlor-alkali production characteristics were incorporated into the analysis. In addition to the venting and combustion scenarios, to deal with the multi-functionality of the chlor-alkali processes that simultaneously produce chlorine, sodium hydroxide, and hydrogen, two different co-product allocation strategies were adopted—mass allocation and market value allocation. It was estimated that by-product hydrogen production from chlor-alkali processes creates 1.3–9.8 kg CO2e/kg H2 of life-cycle GHG emissions on average, which is 20–90% less than the conventional central SMR pathway. The results vary with co-product treatment scenarios, regional electric grid characteristics, on-site power generation, product prices, and hydrogen yield. Despite the variations in the results, it was concluded that the life-cycle GHG emission reduction benefits of using by-product hydrogen from chlor-alkali processes are robust. With a diverse set of scenario analyses, the study developed a comprehensive and detailed life-cycle GHG emissions inventory of the chlor-alkali by-product hydrogen pathway and quantified sensitivity indices in the context of different assumptions and input parameter values.