Greenhouse Gas Emission Inventories Research Articles

Estimating Regional Methane Emission Factors from Energy and Agricultural Sector Sources Using a Portable Measurement System: Case Study of the Denver-Julesburg Basin.

Methane (CH4), a powerful greenhouse gas (GHG), has been identified as a key target for emission reduction in the Paris agreement, but it is not currently clear where efforts should be focused to make the greatest impact. Currently, activity data and standard emission factors (EF) are used to generate GHG emission inventories. Many of the EFs are globally uniform and do not account for regional variability in industrial or agricultural practices and/or regulation. Regional EFs can be derived from top–down emissions measurements and used to make bespoke regional GHG emission inventories that account for geopolitical and social variability. However, most large-scale top–down approaches campaigns require significant investment. To address this, lower-cost driving surveys (DS) have been identified as a viable alternative to more established methods. DSs can take top–down measurements of many emission sources in a relatively short period of time, albeit with a higher uncertainty. To investigate the use of a portable measurement system, a 2260 km DS was conducted throughout the Denver–Julesburg Basin (DJB). The DJB covers an area of 8000 km2 north of Denver, CO and is densely populated with CH4 emission sources, including oil and gas (O and G) operations, agricultural operations (AGOs), lakes and reservoirs. During the DS, 157 individual CH4 emission sources were detected; 51%, 43% and 4% of sources were AGOs, O and G operations, and natural sources, respectively. Methane emissions from each source were quantified using downwind concentration and meteorological data and AGOs and O and G operations represented nearly all the CH4 emissions in the DJB, accounting for 54% and 37% of the total emission, respectively. Operations with similar emission sources were grouped together and average facility emission estimates were generated. For agricultural sources, emissions from feedlot cattle, dairy cows and sheep were estimated at 5, 31 and 1 g CH4 head−1 h−1, all of which agreed with published values taken from focused measurement campaigns. Similarly, for O and G average emissions for well pads, compressor stations and gas processing plants (0.5, 14 and 110 kg CH4 facility−1 h−1) were in reasonable agreement with emission estimates from intensive measurement campaigns. A comparison of our basin wide O and G emissions to measurements taken a decade ago show a decrease of a factor of three, which can feasibly be explained by changes to O and G regulation over the past 10 years, while emissions from AGOs have remained constant over the same time period. Our data suggest that DSs could be a low-cost alternative to traditional measurement campaigns and used to screen many emission sources within a region to derive representative regionally specific and time-sensitive EFs. The key benefit of the DS is that many regions can be screened and emission reduction targets identified where regional EFs are noticeably larger than the regional, national or global averages.

The study of greenhouse gas emissions in village level to support the “PROKLIM” program: case Study of Poncosari Village, Yogyakarta - Indonesia

In Indonesia, PROKLIM is one of the major adaptation and mitigation actions that conducted at the local (community) level. The activities that need to be accelerated and capacity building and mainstreamed in various development activities and existing community activities to support the green house gases (GHG) reduction at national level. The general purpose of this activity is to strengthen the program in increasing understanding about climate change and its various impacts and encourage implementation of real actions in the community. To support this goal, an inventory of greenhouse gas emissions was carried out at the village level, one of which was Poncosari Village located in Bantul Regency, Special Region of Yogyakarta, Indonesia. The GHG emissions inventory is carried out for the domestic, transportation, and livestock sectors. The inventory is carried out by surveying each hamlet in the village. The results of the analysis show high emissions from the livestock sector. The contribution of the domestic sector occupies the second position due to the use of firewood.

COVID-19 impact on an academic Institution's greenhouse gas inventory: The case of Cornell University

Controlling greenhouse gas (GHG) emissions under rapid economic development is a major global challenge and must be addressed in order to avoid major impacts of climate change. Therefore, the accounting of GHG emissions is an important basis for regional climate change mitigation plans. In order to work towards achieving this, a standardization of GHG emissions accounting methodologies should be developed, which will promote a deep decarbonization at different geographical scales. This study builds a complete GHG emissions inventory of the Cornell University campus, quantifying the university's Scope 1, 2, and 3 GHG emissions and identify the main emissions sources. use an EIO-LCA model to investigate the GHG emissions connected to the campus procurement system. The impact of COVID-19 is explored from the perspectives of campus energy systems, transportation, and products & services consumption, which helped to determine the driving forces of GHG emissions fluctuation during the pandemic. Results show that overall, Scope 3 emissions contributed to the largest share of Cornell's GHG emissions (60.4%), followed by Scope 1 (37.8%) and Scope 2 (1.7%). The total GHG emissions of Cornell University in 2019 and 2020 were 463.5 and 404.7 thousand metric tons CO 2 e, respectively. During the COVID pandemic, the campus GHG emissions dropped by 10.99% in 2020 when compared to the 2019 level. When compared to 2019, 2020 Scope 1 GHG emissions reduced by 8.9%, Scope 2 GHG emissions increased by 39.5% and Scope 3 dropped by 16.1%. This study provides a comprehensive GHG accounting framework for universities in order to reach sustainable and carbon-neutral campus targets and analyzes the impact of unpreceded crises on campus life and the environment. • Rigorous quantification of Scope 1, 2, and 3 GHG emissions of a university. • EIO-LCA applied to analyze the GHG emissions of the procurement system. • The impact of COVID-19 on campus GHG emissions are discussed in detail. • Driving forces of COVID-induced GHG emissions change are studied.

How Different and How Alike? Cluster Analysis Applied to Greenhouse Gas Emissions Inventory Data from Companies Listed on the Brazilian Stock Exchange

Purpose: The purpose of this investigation is to understand how companies listed on the B3 that disclose emissions inventories in Brazil are similar or different, based on quantitative variables related to GHG (Greenhouse Gas) emissions intensity, company size, net operating revenue, potential for investments in new technologies, communication, and socio environmental responsibility. Theoretical framework: Theoretical framework addresses corporate social responsibility (RSE) and the economic foundations of Regulation. Method/design/approach: We used a multivariate cluster analysis technique on a sample of 31 companies listed on the Brazilian stock exchange that disclosed emissions inventories over the period 2012 to 2019. Results and conclusion: The results showed that companies like Petrobras (cluster 4), as well as JBS, Vale, Ultrapar and CBD (cluster 3), besides emitting more GHGs, are also larger companies, with higher revenues, committed to communication and socio-environmental responsibility. In addition, they incentivize their executives through higher monetary incentives. Because they have such distinct characteristics from other companies, these companies or sectors could be driven by incentives other than traditional regulation. Research implications: The results suggest that large companies have, in some cases, anticipated regulation as they have incorporated environmental programs within their long-term strategies. In contrast, increased regulation may put pressure on smaller companies to adapt. Originality/value: Our findings contribute to the literature by highlighting the characteristics of these companies that voluntarily disclose emissions inventories in Brazil. Furthermore, we indicate how they are similar or different according to financial, environmental, and social performance criteria.

Greenhouse gas emissions from municipal wastewater treatment facilities in China from 2006 to 2019

Wastewater treatment plants (WWTPs) alleviate water pollution but also induce resource consumption and environmental impacts especially greenhouse gas (GHG) emissions. Mitigating GHG emissions of WWTPs can contribute to achieving carbon neutrality in China. But there is still a lack of a high-resolution and time-series GHG emission inventories of WWTPs in China. In this study, we construct a firm-level emission inventory of WWTPs for CH4, N2O and CO2 emissions from different wastewater treatment processes, energy consumption and effluent discharge for the time-period from 2006 to 2019. We aim to develop a transparent, verifiable and comparable WWTP GHG emission inventory to support GHG mitigation of WWTPs in China.

LIFECYCLE CARBON FOOTPRINT: THE CASE STUDY OF THE ELECTRICITY USE IN PUEBLA, MEXICO

Greenhouse gas emissions inventories and carbon footprints assessed at the local level are critical for any country, mainly for those countries which are part of the Paris Agreement such as Mexico, where federal and local governments join forces to design climate-change mitigation policies. However, determining carbon footprints is time and resource-intensive and not always possible for local governments. To meet this need, we propose an alternative method using lifecycle input-output analysis and location quotients to quantify direct and total emissions of the Mexican state of Puebla caused by its use of electricity during 2013. We quantify the emissions from the production and consumption-based perspective, finding that Puebla’s economy emitted a total of 15 million metric tons of CO2e caused by industrial sectors’ electricity use, which represented 3 % of the total national emissions caused by Mexico’s industrial electricity use. The most significant contributors to Puebla’s total greenhouse gas emissions were the “food and beverage preparation services” and the “business support services” sectors accounting for 38 % and 9 % of Puebla’s total emissions and 50 % and 23 % of direct emissions, respectively. We conclude that, in addition to the decarbonization of the energy matrix, potential climate change mitigation policies should reduce the intensity factors of the sectors with the highest emissions identified with the proposed method.

Artificial Intelligence Approach for Estimating Dairy Methane Emissions.

California's dairy sector accounts for ∼50% of anthropogenic CH4 emissions in the state's greenhouse gas (GHG) emission inventory. Although California dairy facilities' location and herd size vary over time, atmospheric inverse modeling studies rely on decade-old facility-scale geospatial information. For the first time, we apply artificial intelligence (AI) to aerial imagery to estimate dairy CH4 emissions from California's San Joaquin Valley (SJV), a region with ∼90% of the state's dairy population. Using an AI method, we process 316,882 images to estimate the facility-scale herd size across the SJV. The AI approach predicts herd size that strongly (>95%) correlates with that made by human visual inspection, providing a low-cost alternative to the labor-intensive inventory development process. We estimate SJV's dairy enteric and manure CH4 emissions for 2018 to be 496-763 Gg/yr (mean = 624; 95% confidence) using the predicted herd size. We also apply our AI approach to estimate CH4 emission reduction from anaerobic digester deployment. We identify 162 large (90th percentile) farms and estimate a CH4 reduction potential of 83 Gg CH4/yr for these large facilities from anaerobic digester adoption. The results indicate that our AI approach can be applied to characterize the manure system (e.g., use of an anaerobic lagoon) and estimate GHG emissions for other sectors.

Greenhouse Gas Emissions Inventory of a University in the Philippines: the Case of UP Cebu

Estimating the carbon emission of a university is a key step towards carbon neutrality in the education sector and in contributing to the national greenhouse gas emission (GHG) inventory. Following the guidelines of the Philippine Climate Change Commission (CCC), this study examined the university GHG profile using the University of the Philippines Cebu (UPC) as a case study. The main goals were to create a GHG inventory that could serve as a model for other educational institutions in the Philippines and evaluate mitigation strategies that could potentially reduce emissions. Total emission of UPC in 2018 was estimated to be 1,520.6 tCO2e, equivalent to 1.1 tCO2e/capita/yr. The highest contributor to the UPC emission was student mobility, which accounted for 47.2% (717.5 tCO2e) of the total. As the university progressed through the K-12 transition years and assuming a business-as-usual scenario, it was projected that GHG emission had increased by 9.1% (151.4 tCO2e) in 2019 and by 13.6% (238.3 tCO2e) in 2020. If UPC had mitigated its emission in 2018 such as reducing its purchased electricity consumption to 7.5% by shifting to solar energy, total emission could have been reduced by 1.8% or 27.4 tCO2e. If there had been 10% less travels such as by opting to videoconferencing, UPC could have reduced its emission by 0.3% or 5.2 tCO2e. Finally, if UPC had reduced 10% of its solid waste disposal to landfills such as by recycling, carbon emission would have been lessened by 0.3% or 4.7 tCO2e. Through this research, UPC is the first national university in the Philippines to measure its carbon emissions using CCC guidelines. An understanding of the university carbon footprint could significantly raise awareness among stakeholders of their roles and responsibilities in creating a sustainable campus. Moving forward, it is recommended that the inventory would be continued for the succeeding years.

Greenhouse gas emissions inventory data acquisition and analytics for low carbon cities

This paper studied greenhouse gas inventory data acquisition and analytics for municipalities in Thailand. A complete and transparent GHG inventory of eight municipalities was developed to document the current situation, and to help decision-makers to clarify their priorities for reducing greenhouse gas emissions. The Global Protocol for Community-Scale Greenhouse Gas Emissions Inventories guidelines was used to investigate and calculate the greenhouse gas emissions and assess data accuracy. The results indicated that the data source, data format, and data collection of each municipality are relatively similar. Moreover, the activity data needed to be obtained from several authorities. The results showed that Nonthaburi Municipality had the highest greenhouse gas emissions at 2,286,838 tCO2e/yr and Buriram Municipality, the lowest at 239,795 tCO2e/yr. On a per-capita basis, Lamphun Municipality was the highest with 10.1 tCO2e/capita and Buriram Municipality the lowest with 3.8 tCO2e/capita. The results suggest that the municipalities should continually develop a GHG database by creating a routine procedure. An information management system should be produced in the shape of big data which can lead to state policies, plans, and actions for city development to ensure the reduction of greenhouse gas emissions. This in turn will lead to a low carbon city.

China's changing city-level greenhouse gas emissions from municipal solid waste treatment and driving factors

With cities’ intertwined challenges of garbage siege and climate change, it is imperative to explore the greenhouse gas (GHG) emissions from municipal solid waste (MSW) treatment and the determinants of the emissions change. However, related quantitative analysis with high spatial resolution in China has been lacking, which hinder tailored policymaking. To fill the gap, this study develops a long time-series inventory of GHG emissions (including CH4, CO2 and N2O) from MSW for 294 Chinese prefecture-level cities. The temporal and spatial logarithmic mean divisia index (LMDI) model is further used to reveal the drivers behind the emissions change and difference. Results showed that domestic GHG emissions from MSW treatment increased from 39.24 Mt CO2e in 2006 to 128.81 Mt CO2e in 2019, 63.41%-88.95% of which were CH4 emissions accounting for 8.13%-10.22% of China's total CH4 emissions. First-tier cities and new first-tier cities (6.44%) contributed 35.44% to the national emissions in 2019. Furthermore, the national increased emissions were primarily driven by economic output (66.09%), while the MSW treatment intensity per GDP caused emissions reduction by 5.23%. The spatial decomposition verified that the population size was the dominant driving factor for differences between the national average and city-level emissions. Improvements in MSW treatment structure may be the effective abatement strategy for cities in Northwestern China (e.g., Yinchuan, Xining and Lanzhou). These findings could provide insights into the GHG emission mitigation of cities’ MSW sector for a future carbon-neutral society.

Trends in household energy-related GHG emissions during COVID-19 in four Chilean cities

The coronavirus disease 2019 (COVID-19) pandemic has strongly affected economies and human lifestyles globally. The changes observed in domestic energy consumption patterns have had an impact on household greenhouse gas (GHG) emissions. Since GHG emissions inventories are only available at the country level and at annual intervals, most studies have calculated the local emission variations by extrapolating annual emissions with smaller time and territorial scale consumption data. This research presents a bottom-up method, based on the exploitation of a survey addressed to 1200 households, that provides the information to calculate directly the variation in their energy-related GHG emissions, without the need for extrapolations. This method has been applied to four medium-sized Chilean cities with serious air quality problems. Given the high correlation between atmospheric pollutants such as NOx and CO2 emissions, we estimate that before the appearance of COVID-19, per capita CO2 emissions were already high. The results show that space heating-related GHG emissions have increased moderately (between 1 and 6%), while emissions from electricity and gas consumption for non-heating uses have increased significantly (between 8 and 23%). This has harmed the household economy, highlighting the importance of considering socioeconomic aspects when assessing the impact of COVID-19 in its entirety.

Estimated Greenhouse Gas Emissions from PFAS Treatment of Maine Drinking Water

State law requires the adoption of a maximum contaminant level (MCL) for PFAS contamination in drinking water by June 1, 2024. While discussion of mitigation options has included the degree of risk reduction and the cost of treatment, indirect environmental effects are missing from the conversation. Until other technologies are developed, water treatment in Maine will likely rely on the established, energy-intensive method of PFAS adsorption (binding) to granular activated carbon. We conducted an inventory of greenhouse gas emissions associated with water treatment using this treatment media to fill gaps in the discussion. We found that greenhouse gas emissions for water treatment to bring PFAS down to the current interim standard are substantial, raising the footprint of an average user by 6.7–18 percent. We use this information to discuss implications for policymaking.

The Emissions and Measures in Greenhouse Gases Management for Climate Change Mitigation in Developing Countries: A Case of Ho Chi Minh City, Vietnam

Vietnam will achieve net-zero greenhouse gases (GHG) emissions by 2050. Ho Chi Minh City (HCMC) has a considerable amount of GHG emissions (accounted for 20,68% of total GHG in Vietnam). The main GHG sources in HCMC are mainly due to the numerous private vehicles used and the increasing rate of factories. Therefore, to reduce the GHG of the city from these two sources, the bottom-up GHG detailed emission inventory (EI) for major sources must be carried out to determine the potential GHG emission sources. The objectives of this research are 1) to develop detailed GHG EI for HCMC and 2) to develop measures to reduce GHG for HCMC. It is the first bottom-up GHG emission inventory study that applied the EMISENS model to calculate the GHG emission from traffic and industrial sources. The total GHG emission of HCMC in 2019 was 58,272,149 tons CO2eq/year. The primary emission of GHG in HCMC is from on-road traffic (13,484,958 tons CO2eq/year) and the industry sector (17,612,942 tons CO2eq/year). Motorcycles contribute the highest (63%) GHG emission from on-road transportation, whereas the chemical industry contributes the highest (63%) GHG emission from industry sources, followed by the sectors of Paper Production (17.3%), Textile (16.1%), and Metal production (14.7%). The study also developed technical and management solutions to achieve the goal of GHG emission reduction for HCMC and contribute to the National target of net-zero GHG. The main management solutions are based on implementing a Carbon Reporting System for industries and buildings in the city.

Low Carbon Diet: Integrating Gastronomy Service Emissions into the Carbon Management of the University of Graz

To avert the upcoming crisis of climate change, significant changes on different scales and sectors are necessary. The knowledge and research of the higher education sector is an essential part in the fight against climate change already. Many universities admit the urgency of acting within their institution as well and have started to measure their impact on the environment to formulate emission-reduction goals. As part of its sustainability strategy, the University of Graz launched the Institutional Carbon Management (ICM) project to calculate its emissions via a greenhouse gas emissions inventory. In comparison to other inventories, the ICM also includes the gastronomy services on and around the campus of the University of Graz, which is also the focus of this paper. It was found that especially energy- and carbon-intensive food products such as meat and dairy contribute to the emissions of a gastronomy service. In total, the gastronomy service emissions contribute 1.1% to the total emissions inventory of the university. Although the contribution is a rather small portion, the University of Graz sees itself responsible for all its emissions and therefore also aims to gain comprehensive insights into all sub-areas of its institution to formulate validated reduction pathways. The changes to a more sustainable gastronomy and low-emission diets can therefore be seen as part of a wider change towards more environmentally friendly behaviour in general with the overall aim to meet the Paris climate goal.

Multi-Scale GHG Emission Relations in Resource-Based Heavy Industrial Cities: A Case Study of Tangshan City, Hebei Province

The greenhouse gas (GHG) emission pressure faced by resource-based heavy industrial cities was mainly induced by multi-scale interactions, which require systematical assessments from local, regional, national and global scales. Taking Tangshan city, a heavy industry base in Hebei Province of China, as the research area, this study carried out a multi-scale analysis on the GHG emissions in terms of final demand, final consumption and trade balance. The main results are as follows: (1) The average embodied intensity of GHG emissions in Tangshan was 27.6 tons/10,000 CNY, of which 66.2% was caused by local inputs; (2) The secondary industry was the main source for the relatively high GHG emissions in Tangshan; (3) The GHG emissions embodied in final demand were 201.6 million tons, within which the proportion of fixed capital formation reached 59.4%; (4) As for the trade balance, Tangshan was a net exporter of embodied GHG emissions, with the total net outflows of 411.6 million tons. Depicting the GHG emission flows and sorting out the multiple GHG emission inventory would be helpful to identify the transformation pressure of resource-based heavy industry cities, which would be significant for the adjustments in industrial structures and policy optimization of energy saving and emissions reduction.

Energy greenhouse gas emission inventory in Batu City

The development of the tourism sector in Batu City is in line with the development of non-agricultural activities in Batu City that dominates 66.7% of Batu City’s land use pattern. This pattern is related to the energy demand in Batu City and contributes to the increasing GHG emissions from the energy sector. The energy sector contributes 24-25% of GHG emissions and it will increase along with further development of activities. The GHG emission inventory is an important step related to GHG emission reduction, and, due to the uncertainty of GHG emission distribution, the inventory was based on the sources of emission. The main purpose of this research is to make an inventory of the amount of GHG emission from the energy sector in Batu City from 3 main emission sources in Batu, namely transportation, commercial, and household. The analytical method used is the Tier 1 approach using a database of energy consumption and the number of activities as an emission source. The results show that the total amount of GHG emissions from the energy sector in Batu City is 2,562,159,822,007.89 kg/year with an average increase of 0.75% per year and is dominated by emission sources from the household sector. The average increase in GHG emissions from the transportation sector is 58.83% with a significant increase in 2015. In the commercial sector, the average annual increase in GHG emissions is 3.83%, and the household sector—as the largest energy consumer—has an average increase in GHG emissions each year of 0.75%.

Greenhouse Gas Emissions Analysis Working toward Zero-Waste and Its Indication to Low Carbon City Development

Low carbon city development and greenhouse gas (GHG) emission mitigation in urban communities are urgent. There is great potential to improve the GHG inventory at the community level. Meanwhile, building zero-waste cities and improving waste treatment efficiency have been significant environmental issues due to the rapid increase of waste generation. This research aims to develop a community-scale GHG emission inventory of the waste sector and improve its accuracy and consistency through applying the bottom-up approach. This study covers both direct and indirect emissions categories of the waste sector with the goal of building a zero-waste community. Honjo Waseda community, located in Japan, was used as a case study community. Energy consumption waste treatment sectors were evaluated and calculated through first-hand field data. GHG emission estimation of the waste sector included waste incineration, residential wastewater, and waste transport. The highest emissions originated from Beisiagate supermarket due to the large waste amount produced, and the CO2-biomass carbon emissions reached approximately 50% of the total emissions. Furthermore, a quantitative analysis of the implementation of new technologies was also conducted. This study created proposals for GHG emission reduction toward a zero-waste community through the comparison of three cases. Case 1 was business as usual; Case 2 proposed a combination of incineration bio-gasification (MBT); Case 3 introduced a combination of solid recovered fuel (SRF) and a bio-gasification system. SRF contributed the most to emission reduction, and Case 3 exhibited the highest energy recovery. Furthermore, comparing the GHG emissions produced by the use of SRF for power generation and heat supply revealed that using SRF as a heat supply reduced more GHG emissions than using SRF for power generation.

Emisi Gas Rumah Kaca Sektor Pertanian di Kabupaten Tuban: Inventarisasi dan Potensi Aksi Mitigasi

The agricultural sector is one of the contributors to greenhouse gas emissions in Indonesia. The inventory of greenhouse gases in the agricultural sector is not only carried out on land management, but also in the livestock sub sector. Tuban Regency, East Java Province has great potential to contribute to greenhouse gas emissions in the agricultural sector considering that the area of agricultural land and livestock population in this area is very high. This study aims to carry out an inventory of greenhouse gas emissions in the agricultural sector and potential mitigation actions in the same sector. The results of the research are expected to provide input for the Tuban Regency Government in designing mitigation actions that are feasible to implement. The greenhouse gas emission inventory is calculated using Tier-1 IPCC (International Panel on Climate Change) 2006 guidelines by multiplying activity data with emission factors according to IPCC standards. Activity data used for calculating GHG emission comes from secondary data. Meanwhile, the mitigation options obtained from interviews with representatives of farmer groups in Tuban Regency .The results show that the greenhouse gas emissions of the agricultural sector in Tuban Regency in 2019 is 1,665.67 Gg CO2-eq with details of the agricultural sub-sector of 1,092.50 Gg CO 2 -eq and the livestock sub-sector of 573.17 Gg CO 2 -eq. In the agricultural sub-sector, Plumpang Subdistrict occupies the top position as a contributor to greenhouse gas emissions and Tuban Subdistrict is the lowest position. Meanwhile, in the livestock sub-sector, Kerek subdistrict occupies the top position in contributing to GHG emissions and the lowest is in Tuban subdistrict. Through the implementation of balanced fertilization mitigation options and the use of low-emission rice varieties, the GHG emission in Tuban Regency can be reduced by up to 156,43 Gg CO2-eq. Both options are selected by farmers because it is easier and cheaper without relying on others.

Global Covenant of Mayors, a dataset of greenhouse gas emissions for 6200 cities in Europe and the Southern Mediterranean countries

Abstract. The Paris Agreement has underlined the role of cities in combating climate change. The Global Covenant of Mayors for Climate & Energy (GCoM) is the largest international initiative dedicated to promoting climate action at a city level, covering globally over 10 000 cities and almost half the population of the European Union (EU) by end of March 2020. The fifth Intergovernmental Panel on Climate Change (IPCC) report notes that there is a lack of comprehensive, consistent datasets of cities' greenhouse gas (GHG) emission inventories. In order to partly address this gap, we present a harmonised, complete and verified dataset of GHG inventories for 6200 cities in European and Southern Mediterranean countries, signatories of the GCoM initiative. To complement the reported emission data, a set of ancillary data that have a direct or indirect potential impact on cities' climate action plans were collected from other datasets, supporting further research on local climate action and monitoring the EU 27 (the 27 member states of the EU) progress on Sustainable Development Goal (SDG) 13 on climate action. The dataset (Kona et al., 2020) is archived and publicly available with the DOI https://doi.org/10.2905/57A615EB-CFBC-435A-A8C5-553BD40F76C9.

Keeping Track of Greenhouse Gas Emission Reduction Progress and Targets in 167 Cities Worldwide

Actions in cities shape the outcome of greenhouse gas (GHG) emission mitigation and our climate change response. Accurate and consistent carbon inventories are essential for identifying the main sources of emissions and global comparison of carbon reduction progress and would help inform targeted policies for low-carbon transition. To identify the effectiveness of historical carbon reduction policies, our study conducted energy-related GHG emission inventories for 167 globally distributed cities with information from different sectors, and assessed the city-scale near-term, mid-term, and long-term goals carbon mitigation targets from 2020 to 2050. On this basis, we propose mitigation strategies to achieve local and global climate targets. We found that, although Asian cities are the biggest carbon emitters in totals, the per capita GHG emissions of cities in developed countries are still generally higher than that in developing countries. In terms of sectors, the GHG emissions from the stationary energy uses (such as residential, commercial, and industrial buildings) and transportation sector contributed the most. However, cities in more developed nations have been inclined to set absolute carbon reduction targets before 2050, while intensity reduction target has been largely set for cities at the stage of rapid economic growth and accelerated industrialization. More ambitious and easily-tracked climate targets should be proposed by cities and more effective measures of reducing GHG emissions are required to stay consistent with the global ambition of climate change mitigation.