Journal articles on the topic 'City CO2 Emissions'
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1
Kong, Yawen, and Shuguang Liu. "Spatio-temporal Evolution and Driving Factors of Carbon Dioxide Emissions from Energy Consumption in the Yellow River Basin." Journal of Physics: Conference Series 2468, no. 1 (April 1, 2023): 012124. http://dx.doi.org/10.1088/1742-6596/2468/1/012124.
Abstract:
Abstract Based on the data of 57 cities in the Yellow River Basin (YRB) during 2006-2019, this study analyzes its spatio-temporal evolution of carbon dioxide (CO2) emissions from energy consumption, and decomposes its CO2 emissions changes into five factors. The results indicate that: (1) The CO2 emissions in the Yellow River Basin has increased but did not reach the peak from 2006 to 2019, which showed a spatial distribution pattern of “high in the east and low in the west”, with Baotou city, Taiyuan city, Xi’an City, Zhengzhou City and Zibo city forming several high CO2 emission centers of different sizes and spreading to the periphery; (2) The CO2 emission center of gravity in the Yellow River Basin shifted to the southeast as a whole. Ningxia Hui Autonomous Region and Lanzhou city were the main engine provinces and cities to promote its shift. (3) The driving factors of CO2 emissions growth are economic development level, population size and energy efficiency, while industrial structure and clean energy utilization level (CO2 emission coefficient) factors restrained the growth of CO2 emissions in the Yellow River Basin.
2
Budihardjo, Mochamad Arief, Isaaf Fadhilah, Natasya Ghinna Humaira, Mochtar Hadiwidodo, Irawan Wisnu Wardhana, and Bimastyaji Surya Ramadan. "Forecasting Greenhouse Gas Emissions from Heavy Vehicles: A Case study of Semarang City." Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan 18, no. 2 (July 29, 2021): 254–60. http://dx.doi.org/10.14710/presipitasi.v18i2.254-260.
Abstract:
In Indonesia, transportation sector, specifically road transport consumed most energy compared to other sectors. Eventually, the energy consumption will increase due to the growth of vehicle number that also escalate emission. Vehicle emissions had been recognized as a significant contributor to atmospheric greenhouse gas (GHG) pollution. Heavy-duty vehicles are considered as main sources of vehicular emissions in most cities. Therefore, it is crucial to take into account heavy-duty vehicle emission projections in order to support policymakers to identify vehicle emissions and develop pollution control strategies. The aim of this study is to forecast heavy-duty vehicle population, vehicle kilometers travelled (VKT), fuel consumption, and heavy-duty vehicle emissions using data of Semarang City to illustrate greenhouse gas emission of big cities in Indonesia. Business as Usual (BAU) and The Intergovernmental Panel on Climate Change (IPCC) method were incorporated to determine vehicle emission projection. Heavy-duty vehicle emissions increase from 2021 to 2030 by 12.317 to 22.865 Gg CO2/year with amount trucks and buses emissions of 21.981,5 Gg CO2/year and 884,2 Gg CO2/year, respectively.
3
Wang, Yan, and Guangdong Li. "Mapping urban CO2 emissions using DMSP/OLS ‘city lights’ satellite data in China." Environment and Planning A: Economy and Space 49, no. 2 (July 28, 2016): 248–51. http://dx.doi.org/10.1177/0308518x16656374.
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China, the world’s top CO2 emitter, is faced with pressure of energy-saving emission reduction. In the 2015 Paris Climate Conference (COP21), China announced its plan, aiming to cut down CO2 emissions by 60%–65% per unit of GDP in comparison to 2005’s level by 2030. To achieve this ambitious goal, reliable national, provincial, and city-level statistics are fundamental for multi-scale mitigation policy-makings as well as for the allocation of responsibilities among different administrative units. However, China implemented a top-down energy statistical system. The National Bureau of Statistics only publishes annually both national and provincial energy statistics. Only part of cities released their statistics, which results in missing data in city-level energy statistics. This also affects data transparency and accuracy of energy and CO2 emission statistics, and as a result, increases difficulty in allocation of CO2 emission reduction responsibilities. In order to fill this lacuna, we employed a standardized remote sensing inversion approach for estimating China’s city-level CO2 emissions from energy consumptions by integrating DMSP/OLS ‘city lights’ satellite data and statistical data. The end product is a map of city-level CO2 emissions in China. The most topping CO2 emitters are located in the major urban agglomerations along the more economically developed eastern coast (e.g. Yangtze River Delta, Beijing–Tianjin–Hebei, Shandong Peninsula, and Pearl River Delta). Other regions with high CO2 emissions are Shanxi and Henan in Central China, as well as the Chengdu–Chongqing and Shaanxi in West China. Regions with low CO2 emissions are western China, and most of Central China and South China.
4
Liu, Weidan, Yuanhe Sun, Weiguang Cai, Yanyan Ke, and Hong Ren. "A Study on the Spatial Association Network of CO2 Emissions from the Perspective of City Size: Evidence from the Yangtze River Delta Urban Agglomeration." Buildings 12, no. 5 (May 7, 2022): 617. http://dx.doi.org/10.3390/buildings12050617.
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City size expansion in China creates substantial economic circulation, which impacts CO2 emissions. Since CO2 production primarily comes from human activities, CO2 emissions are mainly in cities. To achieve China’s carbon neutrality and provide specific implementation guidance for future carbon-reduction policies, it is worth assessing China’s pressure on carbon reduction in the urban aspect. Highly developed social productivity and a market economy lead to a dramatic increase in the interconnection between cities, and the spatial distribution of CO2 emissions emerges in a spatial association. Therefore, it is of great significance to investigate the interaction of CO2 emissions with spatial effects. Taking the Yangtze River Delta urban agglomeration (YRDUA) as the research target area, this paper utilizes city-size indices to construct spatial-association networks of CO2 emissions for the first time. It employs social network analysis to explore the structures of whole networks, clusters, and city nodes. The main results show that: (1) the spatial associations of CO2 emissions in the YRDUA’s cities have become tighter over time. (2) The networks of CO2 emissions in the YRDUA’s cities have noticeable spatial-spillover effects, and the interaction of CO2 emissions between cities is dominant. (3) Nanjing is the paramount “bridge” node in the networks. (4) Nanjing, Hangzhou, Wuxi, Shanghai, Changzhou, Suzhou, Nantong, and Hefei will be the decisive cities for efficient CO2 emission control in the future. Overall, this paper reveals the role of carbon reduction in the YRDUA’s cities and proposes suggestions for establishing a transboundary energy-saving mechanism to improve the efficiency of energy conservation and emission reduction.
5
Song, Weiwei, Zhiyu Zhu, Wanying Yao, Zhi Gao, Ruihan Chen, Yixuan Zhao, Mengying Wang, et al. "Emissions and Absorption of CO2 in China’s Cold Regions." Processes 11, no. 5 (April 26, 2023): 1336. http://dx.doi.org/10.3390/pr11051336.
Abstract:
Energy production and consumption are dominant sources of CO2 emissions. Investigating the amount and characteristics of CO2 emission sources can aid in reducing CO2 emissions from energy-related sectors, which could lead to the development of advanced technologies and ideas for abatement. Cities play a significant role in CO2 emissions, representing a distinctive unit with a specialized energy consumption structure, meteorology, economy, agriculture, forest acreage, etc. Those properties interact and influence CO2 emissions. The city-level emission inventory is an important scientific database helping to investigate emission abatement technologies and establish control strategies. In this study, city-level CO2 emissions and ecological absorption of China’s coldest province are quantified. In the targeted region, winter lasts for about 6 months. Sectors of industry, thermal power generation, and domestic heating are dominant contributors to the total emissions. The provincial CO2 emissions from energy consumption increased gradually, reaching 327.61 million tons in 2019. Cities with strong industrial activities produced higher CO2 emissions. Moreover, the targeted region is a strong agriculture province, with the largest contribution to grain production in China. The absorption of farmland and forest was quantified, at 343.91 and 69.3 million tons in 2019, respectively. The total absorption was higher than the energy-related emissions. This indicated that the targeted region would provide a considerable carbon sink, attributed to the properties of its ecological system. From 2017 onwards, small boilers (single boilers smaller than 32 steam tons) were removed, and hence the emissions were lower than the original value. This study presents the characteristics of CO2 emissions, and reveals the co-benefit of air pollution control on CO2 reduction.
6
Lian, Jinghui, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, et al. "Can we use atmospheric CO2 measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris." Atmospheric Chemistry and Physics 23, no. 15 (August 9, 2023): 8823–35. http://dx.doi.org/10.5194/acp-23-8823-2023.
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Abstract. Existing CO2 emissions reported by city inventories usually lag in real-time by a year or more and are prone to large uncertainties. This study responds to the growing need for timely and precise estimation of urban CO2 emissions to support present and future mitigation measures and policies. We focus on the Paris metropolitan area, the largest urban region in the European Union and the city with the densest atmospheric CO2 observation network in Europe. We performed long-term atmospheric inversions to quantify the citywide CO2 emissions, i.e., fossil fuel as well as biogenic sources and sinks, over 6 years (2016–2021) using a Bayesian inverse modeling system. Our inversion framework benefits from a novel near-real-time hourly fossil fuel CO2 emission inventory (Origins.earth) at 1 km spatial resolution. In addition to the mid-afternoon observations, we attempt to assimilate morning CO2 concentrations based on the ability of the Weather Research and Forecasting model with Chemistry (WRF-Chem) transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend of around 2 % ± 0.6 % per year in annual CO2 emissions over the Paris region. The impact of the COVID-19 pandemic led to a 13 % ± 1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Subsequently, annual emissions increased by 5.2 % ± 14.2 % from 32.6 ± 2.2 Mt CO2 in 2020 to 34.3 ± 2.3 Mt CO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling and high-precision observations, our current capacity can deliver near-real-time CO2 emission estimates at the city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
7
Sari, Erza Guspita, and Muhammad Sofwan. "Carbon Dioxide (CO2) Emissions Due to Motor Vehicle Movements in Pekanbaru City, Indonesia." Journal of Geoscience, Engineering, Environment, and Technology 6, no. 4 (December 30, 2021): 234–42. http://dx.doi.org/10.25299/jgeet.2021.6.4.7692.
Abstract:
Land use has a very close relationship with transportation. Transportation is formed as a result of the interaction between land use and its support system. Good land use supported by good infrastructure will result in good movement as well. Accessibility is one of the supporting factors for good interaction between transportation and land use—the better the land use conditions in an area, the greater the movement in that area. However, the interaction between land use and transportation can cause one of the problems: the increase in carbon dioxide emissions due to the more significant movement of motorized vehicles. Motor vehicles are the most significant contributor to carbon dioxide (CO2) emissions in the world. The further the route traveled by motorized vehicles, the more carbon dioxide (CO2) emissions will increase. This study aims to analyze the average total emission of carbon dioxide (CO2) resulting from transportation activities in Pekanbaru City into two parts, namely: (1) Based on Travel Time (2) Based on the type of vehicle. Vehicle Kilometers of Travel (VKT) and Emission Factors are the primary data in calculating Carbon Dioxide (CO2) Emissions. The research area consists of 12 zones involving 1,342 households in Pekanbaru City. Based on travel time, 52% of community motorized vehicle movement activities are carried out in the morning. Private cars contribute 65% of carbon dioxide (CO2) emissions in Pekanbaru City based on the type of vehicle. This study found that a high number of motorized vehicles cannot be used as a benchmark that the resulting emissions will also be high. However, the emission of carbon dioxide (CO2) depends on the fuel consumption of each vehicle. The higher the fuel consumption, the higher the amount of carbon dioxide (CO2) emissions released by motorized vehicles.
8
Li, Shuangzhi, Xiaoling Zhang, Zhongci Deng, Xiaokang Liu, Ruoou Yang, and Lihao Yin. "Identifying the Critical Supply Chains for Black Carbon and CO2 in the Sichuan Urban Agglomeration of Southwest China." Sustainability 15, no. 21 (October 31, 2023): 15465. http://dx.doi.org/10.3390/su152115465.
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Black carbon (BC) and CO2 emissions are the two major factors responsible for global climate change and the associated health risks. Quantifying the impact of economic activities in urban agglomerations on BC and CO2 emissions is essential for finding a balance between climate change mitigation and pollution reduction. In this study, we utilized a city-level environmental extended multi-regional input–output model (EE-MRIO), integrated nexus strength (INS), and structural path analysis (SPA) to quantify the BC and CO2 footprints, nexus nodes, and supply chains of 21 cities in the Sichuan urban agglomeration (SUA) from 2012 to 2017. The results revealed that approximately 70% of the BC and CO2 footprints come from inter-city transactions, with Chengdu being the largest importing city, while the supply of other cities was greater than their consumption. The SUA has transitioned from a supply-side city cluster to a consumption-oriented city cluster in its trade with other domestic regions. The SPA analysis highlighted that the construction sector was the largest emitter of downstream BC and CO2, while the electricity supply, metal/nonmetallic manufacture, oil refining and coking, transportation, and extraction industry sectors were the main nexus nodes for BC and CO2 emissions in the SUA. Notably, the reduction in BC emissions was due to decreased indirect emissions from oil refining and coking, while the decrease in CO2 emissions was a result of reduced indirect emissions from electricity supply. This article presents, for the first time, a quantification of the heterogeneous impacts and emission supply chains of BC and CO2 emissions from economic activities in the SUA, providing valuable insights for developing climate mitigation policies tailored to different urban clusters.
9
Tao, Mengchu, Zhaonan Cai, Ke Che, Yi Liu, Dongxu Yang, Lin Wu, Pucai Wang, and Mingzhu Yang. "Cross-Inventory Uncertainty Analysis of Fossil Fuel CO2 Emissions for Prefecture-Level Cities in Shandong Province." Atmosphere 13, no. 9 (September 10, 2022): 1474. http://dx.doi.org/10.3390/atmos13091474.
Abstract:
A series of carbon dioxide (CO2) emission inventories with high spatial resolutions covering China have been developed in the last decade, making it possible to assess not only the anthropogenic emissions of large administrational units (countries; provinces) but also those of small administrational units (cities; counties). In this study, we investigate three open-source gridded CO2 emission inventories (EDGAR; MEIC; PKU-CO2) and two statistical data-based inventories (CHRED; CEADs) covering the period of 2000–2020 for 16 prefecture-level cities in Shandong province in order to quantify the cross-inventory uncertainty and to discuss potential reasons for it. Despite ±20% differences in aggregated provincial emissions, all inventories agree that the emissions from Shandong increased by ~10% per year before 2012 and that the increasing trend slowed down after 2012, with a quasi-stationary industrial emission proportion being observed during 2008–2014. The cross-inventory discrepancies increased remarkably when downscaled to the city level. The relative differences between two individual inventories for half of the cities exceeded 100%. Despite close estimations of aggregated provincial emissions, the MEIC provides relatively high estimates for cities with complex and dynamic industrial systems, while the CHRED tends to provide high estimates for heavily industrial cities. The CHRED and MEIC show reasonable agreement regarding the evolution of city-level emissions and the city-level industrial emission ratios over 2005–2020. The PKU-CO2 and EDGAR failed to capture the emissions and their structural changes at the city level, which is related to their point-source database stopping updates after 2012. Our results suggest that cross-inventory differences for city-level emissions exist not only in their aggregated emissions but also in their changes over time.
10
Shen, Zijie, and Liguo Xin. "Characterizing Carbon Emissions and the Associations with Socio-Economic Development in Chinese Cities." International Journal of Environmental Research and Public Health 19, no. 21 (October 23, 2022): 13786. http://dx.doi.org/10.3390/ijerph192113786.
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Reducing carbon emissions in cities is crucial for addressing climate change, while the city-level emissions of different compositions and their relationships with socio-economic features remain largely unknown in China. Here, we explored the city-level emission pattern from the industrial, transportation, and household sectors and the emission intensity, as well as their associations with socio-economic features in China, using the up-to-date (2020) CO2 emissions based on 0.1° grid (10 × 10 km) emission data. The results show that: (1) CO2 emissions from the industrial sector were considerably dominant (78%), followed by indirect (10%), transportation (8%), and household (2%) emissions on the national scale; (2) combining total emissions with emission intensity, high emission–high intensity cities, which are the most noteworthy regions, were concentrated in the North, while low emission–low intensity types mainly occurred in the South-West; (3) cities with a higher GDP tend to emit more CO2, while higher-income cities tend to emit less CO2, especially from the household sector. Cities with a developed economy, as indicated by GDP and income, would have low emissions per GDP, representing a high emission efficiency. Reducing the proportion of the secondary sector of the economy could significantly decrease CO2 emissions, especially for industrial cities. Therefore, the carbon reduction policy in China should focus on the industrial cities in the North with high emission–high intensity performance. Increasing the income and proportion of the tertiary industry and encouraging compact cities can effectively reduce the total emissions during the economic development and urbanization process.
11
Christiani, Natalia, Yayat Hidayat, and Sutrisno Trisno. "CO2 Emission and Absorption Estimation in Bandung City by Implementing CO2 Emission Rate Reduction Simulation Using the Stella Program." 3BIO: Journal of Biological Science, Technology and Management 3, no. 1 (July 13, 2021): 28–41. http://dx.doi.org/10.5614/3bio.2021.3.1.4.
Abstract:
Bandung CO2 emissions continue to increase in line with its population. The emissions source comes from the industrial, transportation, Liquefied Petroleum Gas (LPG), household, and livestock sectors, whereas CO2 absorption only comes from vegetation through photosynthesis. High CO2 emissions could decrease air quality and reduce environmental health. This study aims to estimate the amount of CO2 emissions and their absorption in Bandung by implementing CO2 Emission Rate Reduction Simulation (CERRS). The simulation comprises four scenarios, namely substitution of vehicle fuel and the application of smart driving techniques, optimization of waste processing in IWPS, processing 90% of livestock waste into biogas, and green space development of 30% of Bandung City area. Estimated CO2 emission and absorption rates were calculated for the next 10 years (2021-2030) using the Stella program version 9.0.2. The results showed that without implementing the CERRS, the amount of CO2 emissions in Bandung in 2030 was estimated to reach 10,983,666.82 tons while implementing the CERRS was 2,361,721.30 tons. Without implementing the CERRS, the estimated amount of CO2 absorptions in 2030 was 214,235.11 tons, while implementing the CERRS was 2,785,703.11 tons. It is expected that the application of the CERRS could reduce the level of CO2 emissions in Bandung by 78.5% and increase CO2 absorptions by 1,200.3%.
12
Hasddin, Hasddin, Abd Azis Muthalib, Edward Ngii, and Asrip Putera. "The Ability of Green Open Spaces in Greenhouse Gas Control to Achieve Green Cities in Kendari City." International Journal of Energy Economics and Policy 12, no. 1 (January 19, 2022): 327–31. http://dx.doi.org/10.32479/ijeep.11980.
Abstract:
The urban challenge in realizing a green city for the purpose of a sustainable city is air pollution resulting from vehicle emissions (Carbon monoxide/ CO2). Reducing vehicle emissions can be done by providing green open spaces. In Kendari City, a potential area for the development of green open space is the Bahteramas General Hospital. Activities in the area and around the Bahteramas General Hospital in Kendari City are quite high so that they contribute to emissions (CO2). The object of research analysis is the number of vehicles (daily traffic), the capacity of electricity use, the area of the Bahteramas General Hospital and the area of the existing green open space. The results showed that the type of vehicle that contributes high to CO2 is a motorcycle. The use of fuel as a source of emission (CO2) which contributes to premium types of greenhouse gases, diesel and the use of electrical energy. The absorption capacity of the existing green open space has not been able to reduce CO2 emissions, so it is necessary to expand the green open space to control greenhouse gases.
13
Meidiana, C., D. H. Leliana, and D. Agustina. "Potential of urban greening for carbon dioxide reduction from transportation sector." IOP Conference Series: Earth and Environmental Science 916, no. 1 (November 1, 2021): 012005. http://dx.doi.org/10.1088/1755-1315/916/1/012005.
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Abstract Various urban activities which exist in different lands uses in Mojokerto City such as settlement, commercial area, public service, and industrial area form the urban dynamic. Urban dynamic is stimulated by some factors including mobility of people and goods, information, and money. People’s mobility which dominates the urban mobility is accommodated by transportation mode causing transportation sector ranks the top first sector contributing to carbon dioxide (CO2) emissions in urban area, including Mojokerto City. Therefore, the study aims to propose reasonable solution for CO2 emissions reduction from transportation sector. The total amount of CO2 emissions is calculated first, and vegetation capacity to absorb CO2 is calculated afterwards using the formula for emission generation and bio capacity respectively. Development of urban greening is proposed to improve the bio-capacity of urban greening to absorb the remaining emissions. Based on the emission calculation, the total amount of CO2 emissions from transportation sector ranges between 6.6 to to 262.1 ton/year depending on the traffic volume and the distance covered by motorized vehicles. Meanwhile, calculation of bio capacity shows that the average absorption of vegetation in Mojokerto City is only 863.91 ton/yr. Improving urban greening area by planting more trees with higher absorption capacity is proposed to absorb the remaining emission. Calculation shows that enhanced urban greening can increase the emission absorption from 4% to 7% of the total emission from transportation sector.
14
Aindo, Nur Rezki, Lies Indriyani, Abdul Manan, La Gandri, and Sahindomi Bana. "Analysis of The Need for Green Open Spaces in Reducing CO2 Carbon Dioxide Emissions in the Bahteramas Hospital Area of Southeast Sulawesi Province." Journal of Soilscape and Agriculture 2, no. 1 (September 30, 2023): 24–32. http://dx.doi.org/10.19184/jsa.v2i1.429.
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This study aims to determine CO2 emissions resulting from transportation sources, residents, electricity and the ability of green open spaces (RTH) to reduce CO2 gas emissions in the Bahteramas Hospital Area. This research was conducted in December 2022-January 2023 at Bahteramas Baruga Hospital, Kendari City, Southeast Sulawesi Province. The results showed that the highest CO2 emission load was generated from the use of electricity with a total of 54,119 kg/day, then population emissions were 4,933 kg/day, while the lowest emission load was generated from CO2 transportation emissions of 4,437 kg/day. The total emission generated in the Bahteramas Hospital Area is 63,489 kg /day. The ability of green open space to reduce CO2 emissions is 8,399 kg/day so that it still has residual CO2 emissions that have not been able to be absorbed by the existing green open space of 55,090 kg/ day.
15
Unzilatirrizqi, Yan El Rizal, Bambang Istiyanto, Haris Ilman Fiqih, and Riska Arsita Harnawati. "Modeling Vehicle Emissions Delivery in Tegal City Road." RSF Conference Series: Engineering and Technology 2, no. 2 (November 29, 2022): 338–47. http://dx.doi.org/10.31098/cset.v2i2.587.
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The problem of carbon dioxide in several cities in Indonesia is getting higher and requires more focused handling. The city of Tegal, one of the cities in Indonesia located on the Pantura route, has a significant impact on the distribution of CO2 emissions. This research was conducted by modeling and mapping the number of emissions on several roads based on the outcomes of transportation efforts in Tegal City. Arc-GIS is used for analysis and modeling, with an approach to calculating emissions based on the number of vehicles, emission factors, and fuel consumption. The results showed that gasoline-fueled cars and other motorized vehicles based on the mapping model became the CO2 suppliers on every road section. The highest emission distribution was observed on the Tegal City pantura road, which is a national transportation route.
16
Rosadi, Dedi, Randhi Saily, Zaiyar Zaiyar, and Ulfa Jusi. "IDENTIFIKASI JEJAK KARBON SKALA RUMAH TANGGA SEBAGAI UPAYA MENGATASI PERUBAHAN IKLIM." INDONESIAN JOURNAL OF CONSTRUCTION ENGINEERING AND SUSTAINABLE DEVELOPMENT (CESD) 5, no. 2 (December 29, 2022): 15–23. http://dx.doi.org/10.25105/cesd.v5i2.15629.
Abstract:
The high level of population density in RT 002 / RW 009 Labuh Baru Timur Village, Payung Sekaki District, Pekanbaru City has the potential to be a contributor to CO2 carbon dioxide emissions. The resulting carbon emissions are from electrical energy and food consumption. The formulation of the problem of this research is how the value of the carbon footprint resulting from the consumption of food and electricity energy. The purpose of this study is to determine the value of carbon emissions. Based on the data obtained, the value of emissions from the electricity sector is 1061.106786 (kg CO2)/day, the food consumption sector is 526.33299 (kg CO2)/day. The highest emission value produced by the electricity sector from the 32nd respondent was 18.39823 (kg C02)/day, and the food consumption sector from the 48th respondent was 13.55319 (kg C02)/day.
17
Vogt, M., E. D. Nilsson, L. Ahlm, E. M. Mårtensson, and C. Johansson. "The relationship between 0.25–2.5 μm aerosol and CO<sub>2</sub> emissions over a city." Atmospheric Chemistry and Physics Discussions 10, no. 9 (September 9, 2010): 21521–45. http://dx.doi.org/10.5194/acpd-10-21521-2010.
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Abstract. Unlike exhaust emissions, non-exhaust traffic emissions are completely unregulated and there are large uncertainties in the non-exhaust emission factors required to estimate the emissions of these aerosols. This study provides the first published results of direct measurements of size resolved emission factors for particles in the size range 0.25–2.5 μm using a new approach deriving aerosol emission factors from the CO2 emission fluxes. Because the aerosol and CO2 emissions have a common source and because the CO2 emission per fuel or traffic amount are much less uncertain than the aerosol emissions, this approach has obvious advantages. Therefore aerosol fluxes were measured during one year using the eddy covariance method at the top of a 118 m high communication tower over Stockholm, Sweden. Maximum CO2 and particle fluxes coincides with the wind direction with densest traffic within the footprint area. Negative fluxes (uptake of CO2 and deposition of particles) coincides with an urban forest area. The fluxes of CO2 were used to obtain emission factors for particles by assuming that the CO2 fluxes could converted to amounts of fuel burnt. The estimated emission factors for the fleet mix in the measurement area are, in number 1.4×1011 [particle veh−1 km−1]. Assuming spherical particles of density 1600 kg/m3 this corresponds to 27.5 mg veh−1 km−1. Wind speed influence the emission factor indicating that wind induced turbulence may be important.
18
Masyruroh, Anis, Djoko M Hartono, Herman Haeruman, and Emir Hadisuganda. "Green Open Space Needs Analysis of Carbon Dioxide (Co2) Gas Emissions Absorbtion in Serang City." International Journal of Engineering & Technology 7, no. 2.29 (May 22, 2018): 917. http://dx.doi.org/10.14419/ijet.v7i2.29.14283.
Abstract:
An increasing number of population in Serang has resulted in the diversion of vegetated land function to be built area, thus reducing total area of green open space (RTH) of the city. Impact of the land conversion increase will occur on the increasing area of land cover. Land cover thus reduced the vegetation ability to absorb CO2, so that the CO2 generated from activities in the city, such as from energy consumption, livestock and landfill waste cannot be absorbed optimally. The purpose of this study were: 1) to analyze the amount of CO2 emissions from energy use, livestock and garbage activities in 2016-2026; 2) to analyze the CO2 absorption by green space area; 3) to analyze RTH Needs of 2016-2026 to absorb CO2. gas emission. This study was conducted in May 2016 to September 2016. The method used in this research was IPCC calculation for the calculation of emissions from garbage, livestock, and electrical energy. Based on the results of the study showed that in 2016 the Serang city need of green space area was 9844.79 hectares to absorb CO2 gas emissions by 511,051.61 and in 2026 green space area needs of Serang city to absorb CO2 emissions by 18.168 tons was a total area of 1,058,468.16, 76 hectares.
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Zhu, Hanxiong, Kexi Pan, Yong Liu, Zheng Chang, Ping Jiang, and Yongfu Li. "Analyzing Temporal and Spatial Characteristics and Determinant Factors of Energy-Related CO2 Emissions of Shanghai in China Using High-Resolution Gridded Data." Sustainability 11, no. 17 (August 31, 2019): 4766. http://dx.doi.org/10.3390/su11174766.
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In this study, we create a high-resolution (1 km x 1 km) carbon emission spatially gridded dataset in Shanghai for 2010 to 2015 to help researchers understand the spatial pattern of urban CO2 emissions and facilitate exploration of their driving forces. First, we conclude that high spatial agglomeration, CO2 emissions centralized along the river and coastline, and a structure with three circular layers are the three notable temporal–spatial characteristics of Shanghai fossil fuel CO2 emissions. Second, we find that large point sources are the leading factors that shaped the temporal–spatial characteristics of Shanghai CO2 emission distributions. The changes of CO2 emissions in each grid during 2010–2015 indicate that the energy-controlling policies of large point emission sources have had positive effects on CO2 reduction since 2012. The changes suggest that targeted policies can have a disproportionate impact on urban emissions. Third, area sources bring more uncertainties to the forecasting of carbon emissions. We use the Geographical Detector method to identify these leading factors that influence CO2 emissions emitted from area sources. We find that Shanghai’s circular layer structure, population density, and population activity intensity are the leading factors. This result implied that urban planning has a large impact on the distribution of urban CO2 emissions. At last, we find that unbalanced development within the city will lead to different leading impact factors for each circular layer. Factors such as urban development intensity, traffic land, and industrial land have stronger power to determine CO2 emissions in the areas outside the Outer Ring, while factors such as population density and population activity intensity have stronger impacts in the other two inner areas. This research demonstrates the potential utility of high-resolution carbon emission data to advance the integration of urban planning for the reduction of urban CO2 emissions and provide information for policymakers to make targeted policies across different areas within the city.
20
Lin, Xiaohu, Jie Ren, Jingcheng Xu, Tao Zheng, Wei Cheng, Junlian Qiao, Juwen Huang, and Guangming Li. "Prediction of Life Cycle Carbon Emissions of Sponge City Projects: A Case Study in Shanghai, China." Sustainability 10, no. 11 (October 31, 2018): 3978. http://dx.doi.org/10.3390/su10113978.
Abstract:
In recent years, China has been vigorously carrying out the planning and implementation of Sponge City. Since the implementation of Sponge City projects involves substantial materials and energy consumption, it is significant to account corresponding carbon emissions and sinks. The existed studies about carbon emission of stormwater management measures, however, are not able to take the whole life cycle and different facilities into consideration. Therefore, this study develops a comprehensive accounting model based on Intergovernmental Panel on Climate Change (IPCC) guidelines and life cycle assessment (LCA) method to predict carbon emissions and carbon sinks of Sponge City projects more comprehensively and accurately. The model is applied to an actual residential community in Shanghai as a case study. Results show that the total indirect carbon emission is estimated to be 774,277 kg CO2 eq during a 30-year lifespan, among which carbon emissions from operation and maintenance phases are 2570 kg CO2 eq/year and 7309 kg CO2 eq/year, respectively, both directly proportional to the service life of the facilities. Three kinds of achievable carbon sinks are carbon sequestration in green space (5450 kg CO2 eq/year), carbon sink from rainwater utilization (15,379 kg CO2 eq/year) and carbon sink from runoff pollutant removal (19,552 kg CO2 eq/year). Carbon neutrality is expected to be reached after approximately 19 years. The established carbon emission accounting model can contribute to better planning and construction of Sponge City in China and enhance further energy conservation and carbon emission reduction.
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Saputra, Rifky Bagus. "Mapping of Carbon Dioxide (Co2) Emissions Due To Increased Vehicle Volume in Mataram City." Jurnal Syntax Transformation 4, no. 10 (October 25, 2023): 54–64. http://dx.doi.org/10.46799/jst.v4i10.832.
Abstract:
The high level of population and activities in the city of Mataram also increases the use of vehicles as a secondary need for the community to help with daily activities in land transportation. As the use of vehicles increases, the demand for fuel oil (BBM) also increases. Fuel is a material that can be converted into energy by burning fuel where the fuel contains heat energy that can be released and manipulated. Vehicle emissions are a major source of pollution in big cities in Indonesia. CO2 is a compound consisting of the elements carbon and oxygen with the writing CO2. Carbon dioxide is a gaseous element that exists at atmospheric temperature and pressure. The hope for this research is to determine CO2 levels in the city of Mataram and prevent CO2 emissions from increasing. The results of calculating the highest vehicle volume are located in segment III Jalan Majapahit of 3506 pcu/hour which occurs at 17:00 - 17:15 WITA. The results of the regression analysis between vehicle volume as the X variable and CO2 gas emissions as the Y variable on the five road segments conducted by the study were y = 134.57 ln(x) - 970.14 with an R2 value of 0.8661 included in the 0.80 interval – 1,000 which means that the strength of the relationship between vehicle volume and CO2 emissions has a very strong relationship and vehicle volume contributes 86.6165% to CO2 emissions. Based on the results of the discussion that was carried out, the CO2 gas emission levels in all road segments carried out had an average CO2 gas emission level value of 103.31 – 108.56 kg/hour.
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Li, Yaqian, Yile Chen, Qi Cai, and Liujun Zhu. "Calculation of CO2 Emissions from China at Regional Scales Using Remote Sensing Data." Remote Sensing 16, no. 3 (January 31, 2024): 544. http://dx.doi.org/10.3390/rs16030544.
Abstract:
Since industrialization, global carbon dioxide (CO2) emissions have been rising substantially, playing an increasingly important role in global warming and climate change. As the largest CO2 emitter, China has proposed an ambitious reduction plan of peaking before 2030 and achieving carbon neutrality by 2060. Calculation of CO2 emissions inventories at regional scales (e.g., city and county) has great significance in terms of China’s regional carbon policies as well as in achieving the national targets. However, most of the existing emissions data were calculated based on fossil fuel consumptions and were thus limited to the provinces in China, making it challenging to compare and analyze the CO2 emissions of different cities and counties within a province. Machine learning methods provided a promising alternative but were still suffering from the lack of availability of training samples at city or county scales. Accordingly, this study proposed to use the energy consumption per unit GDP (ECpGDP) and GDP to calculate the effective CO2 emissions, which are the CO2 emissions if all consumed energy was generated by standard coal. Random forest models were then trained to establish relationships between the remote sensing night-light data and effective CO2 emissions. A total of eight predictor variables were used, including the night-light data, the urbanization ratio, the population density, the type of sensors and administrative divisions, latitude, longitude, and the area of each city or county. Meanwhile, the mean value of the five-fold cross-validation model was used as the estimated effective CO2 emissions in order to avoid overfitting. The evaluation showed a root mean square error (RMSE) of 10.972 million tons and an overall Pearson’s correlation coefficient (R) of 0.952, with satisfactory spatial and temporal consistency. The effective CO2 emissions of 349 cities and 2843 counties in China during 1992–2021 were obtained, providing a promising dataset for CO2-emission-related applications.
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Tan, Xianchun, Tangqi Tu, Baihe Gu, Yuan Zeng, Tianhang Huang, and Qianqian Zhang. "Assessing CO2 Emissions from Passenger Transport with the Mixed-Use Development Model in Shenzhen International Low-Carbon City." Land 10, no. 2 (February 1, 2021): 137. http://dx.doi.org/10.3390/land10020137.
Abstract:
Assessing transport CO2 emissions is important in the development of low-carbon strategies, but studies based on mixed land use are rare. This study assessed CO2 emissions from passenger transport in traffic analysis zones (TAZs) at the community level, based on a combination of the mixed-use development model and the vehicle emission calculation model. Based on mixed land use and transport accessibility, the mixed-use development model was adopted to estimate travel demand, including travel modes and distances. As a leading low-carbon city project of international cooperation in China, Shenzhen International Low-Carbon City Core Area was chosen as a case study. The results clearly illustrate travel demand and CO2 emissions of different travel modes between communities and show that car trips account for the vast majority of emissions in all types of travel modes in each community. Spatial emission differences are prominently associated with inadequately mixed land use layouts and unbalanced transport accessibility. The findings demonstrate the significance of the mixed land use and associated job-housing balance in reducing passenger CO2 emissions from passenger transport, especially in per capita emissions. Policy implications are given based on the results to facilitate sophisticated transport emission control at a finer spatial scale. This new framework can be used for assessing the impacts of urban planning on transport emissions to promote sustainable urbanization in developing countries.
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Nst, Eri Susan, Yulia Fitri, Laras Sita Widara, and Fajri Fajri. "Prediction of CO2 emission based on road density approach." Journal of Aceh Physics Society 12, no. 1 (January 10, 2023): 6–20. http://dx.doi.org/10.24815/jacps.v12i1.27961.
Abstract:
Abstrak. Pekanbaru merupakan kota terbesar di Provinsi Riau dengan pertumbuhan ekonomi yang pesat. Peningkatan ekonomi berpengaruh terhadap perkembangan jumlah trasnportasi kendaraan bermotor di Kota Pekanbaru. Jumlah kendaraan rata-rata meningkat sebesar 7,3% per tahun. Peningkatan sektor transportasi menjadi salah satu penyebab terjadinya kerusakan lingkungan dan pemanasan global serta menurunnya kualitas udara di wilayah perkotaan. Polusi paling dominan yang dihasilkan dari sektor transportasi yaitu karbondioksida (CO2). Tujuan penelitian ini adalah menghitung emisi CO2 dari kendaraan di Kota Pekanbaru. Metode yang digunakan untuk menghitung emisi CO2 yaitu metode IPCC 2006 Guidelines Tier 2 berdasarkan pendekatan kepadatan Jalan. Volume kendaraan didapatkan berdasarkan traffic counting di ruas jalan Kota Pekanbaru. Hasil perhitungan menunjukkan bahwa emisi tertinggi di Kota Pekanbaru berada di ruas jalan nasional yaitu sebesar 11,8 kg CO2/SMP. Penyumbang emisi CO2 di Kota Pekanbaru didominasi oleh jenis kendaraan truk dan bus. Truk menyumbang emisi sebesar 7,9 kg CO2/SMP dan bus menghasilkan emisi sebesar 6,3 kg CO2/SMP. Selanjutnya hasil penelitian juga menemukan bahwa emisi tertinggi yaitu pada hari efektif sebesar 6,84 kg CO2/SMP. Jam tersibuk yang menghasilkan nilai emisi tertinggi yaitu jam puncak sore. Emisi yang dihasilkan dengan nilai sebesar 6,48 kg CO2/SMP. Abstract. Pekanbaru is the largest city in Riau Province with rapid economic growth. The increase in the economy has affected the development of the number of motorized vehicle transportation in Pekanbaru City. The average number of vehicles increased by 7.3% per year. The increase in the transportation sector is one of the causes of environmental damage and global warming as well as declining air quality in urban areas. The most dominant pollution generated from the transportation sector is carbon dioxide (CO2). The purpose of this study was to calculate CO2 emissions from vehicles in Pekanbaru City. The method used to calculate CO2 emissions was the IPCC 2006 Guidelines Tier 2 method based on the road density approach. Vehicle volume was obtained based on traffic counting on Pekanbaru City roads. The calculation results show that the highest emission in Pekanbaru City is on the national road segment, which is equal to 11.8 kg CO2/SMP. The contributors to CO2 emissions in Pekanbaru City are dominated by trucks and buses. Trucks contribute 7.9 kg CO2/SMP and buses emit 6.3 kg CO2/SMP. Furthermore, the results of the study also found that the highest emission was on an effective day of 6.84 kg CO2/SMP. The busiest hour that produces the highest emission value is the afternoon peak hour. Emissions produced with a value of 6.48 kg CO2/SMP.
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Wang, Huaxing, Chuan Chen, Zhiqiao Xiong, and Dandan Li. "How to Achieve Carbon Neutrality in Cities? Evidence from China’s Low-Carbon Cities Development." International Journal of Environmental Research and Public Health 20, no. 3 (January 24, 2023): 2121. http://dx.doi.org/10.3390/ijerph20032121.
Abstract:
Low-carbon city pilots (LCCP) is a key policy for realizing emission peak and carbon neutrality in China, using China’s samples from 280 towns from 2006 to 2016. The article utilizes PSM-DID, mediated effects, and moderating effects approach for validating a CO2 reduction effect, mechanisms, and synergistic elements of LCCP. The regression outcomes suggest that (1) LCCP significantly decreases CO2 emissions levels and average annual carbon emissions in LCCP fall by 2.6 percent. (2) LCCP focus on reducing carbon emissions by increasing R&D investment, the efficiency of energy, and decreasing the high CO2 emissions industry. Among them, the reduction of the high carbon emission industry is mainly FDI, while the reduction of local industry is not obvious. (3) LCCP’s carbon reduction effects suggest a reversed U-shape relationship with city size. Digitalization and marketization of LCCP are crucial to the carbon reduction effect. Carbon reduction and pollution reduction have a strong synergistic effect.
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Purwanto, Christine Prita. "INVENTARISASI EMISI SUMBER BERGERAK DI JALAN (ON ROAD) KOTA DENPASAR." ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) 9, no. 1 (May 1, 2015): 1. http://dx.doi.org/10.24843/ejes.2015.v09.i01.p01.
Abstract:
The growth of population in Denpasar City followed by increasing of transportation facilities that potentially cause pollution by vehicle emissions and cause serious environmental problems and which has adverse effect to the human health. The research aimed to estimate the number and distribution of emission gases on air pollutants, such as: PM10, NOx, SO2, CO, CO2 and HC. The calculation of estimated based on road mobile sources (On Road) in Denpasar City, includes all known sources such as the highway, small roads, terminals, and parking lots. The calculation of emissions is calculated by using the approach of emission estimation method. The total load of emissions by moving source on the street in Denpasar for each pollutant gases are: value of NOx is 3765.89 tons/year , value of SO2 is 212.34 tons/year, value of HC is 20049.87 tons/year, value of PM10 is 444.16 tons/year, value of CO2 is 984,280.21 tons/ year, and value of CO is 55432.04 tons/year. Overall, the total load of pollutant emissions gases of Denpasar City is greater than the total load of pollutant emissions gases in Palembang city. Spatially, the distribution of pollutant gas emissions are not spread evenly. The pollutants emissions of NOx, CO2, and HC for each gases have the highest values are about 115 – 239 tons/year, 26.944 – 4.735 tons/year, and 471 – 954 tons/year distributed at West Denpasar District and Niti Mandala Renon area. The highest pollutans emission of SO2 is about 15,5-44 tons/year, distributed at West Denpasar District. The highest pollutans emission of PM10 is about 11,5-21 tons/year, distributed at West Denpasar District, Badung Market area, Puputan Square area, and Niti Mandala Renon area. The highest CO pollutant emission is about 1277-1912 tons/year, distributed at West Denpasar District, Badung Market area, Puputan Square area, Niti Mandala Renon area, and Udayana University area.
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Wu, Lin, Grégoire Broquet, Philippe Ciais, Valentin Bellassen, Felix Vogel, Frédéric Chevallier, Irène Xueref-Remy, and Yilong Wang. "What would dense atmospheric observation networks bring to the quantification of city CO<sub>2</sub> emissions?" Atmospheric Chemistry and Physics 16, no. 12 (June 24, 2016): 7743–71. http://dx.doi.org/10.5194/acp-16-7743-2016.
Abstract:
Abstract. Cities currently covering only a very small portion ( < 3 %) of the world's land surface directly release to the atmosphere about 44 % of global energy-related CO2, but they are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by the monitoring, reporting, and verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we analyze the potential of a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. This monitoring tool is configured for the quantification of the total and sectoral CO2 emissions in the Paris metropolitan area (∼ 12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. Its performances are evaluated in terms of uncertainty reduction based on observing system simulation experiments (OSSEs). They are analyzed as a function of the number of sampling sites (measuring at 25 m a.g.l.) and as a function of the network design. The instruments presently used to measure CO2 concentrations at research stations are expensive (typically ∼ EUR 50 k per sensor), which has limited the few current pilot city networks to around 10 sites. Larger theoretical networks are studied here to assess the potential benefit of hypothetical operational lower-cost sensors. The setup of our inversion system is based on a number of diagnostics and assumptions from previous city-scale inversion experiences with real data. We find that, given our assumptions underlying the configuration of the OSSEs, with 10 stations only the uncertainty for the total city CO2 emission during 1 month is significantly reduced by the inversion by ∼ 42 %. It can be further reduced by extending the network, e.g., from 10 to 70 stations, which is promising for MRV applications in the Paris metropolitan area. With 70 stations, the uncertainties in the inverted emissions are reduced significantly over those obtained using 10 stations: by 32 % for commercial and residential buildings, by 33 % for road transport, by 18 % for the production of energy by power plants, and by 31 % for total emissions. These results indicate that such a high number of stations would be likely required for the monitoring of sectoral emissions in Paris using this observation–model framework. They demonstrate some high potential that atmospheric inversions can contribute to the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments) and the advantage that could be brought by the current developments of lower-cost medium precision (LCMP) sensors.
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Verma, Ram Lal, and Guilberto Borongan. "Emissions of Greenhouse Gases from Municipal Solid Waste Management System in Ho Chi Minh City of Viet Nam." Urban Science 6, no. 4 (November 7, 2022): 78. http://dx.doi.org/10.3390/urbansci6040078.
Abstract:
Accurate estimation of emissions of greenhouse gases (GHGs) is required for making effective climate change mitigation policies at the national level. Among major sources, municipal solid waste (MSW) is an important source of GHGs, such as methane (CH4), generated during the anaerobic decomposition of organic matter. In Viet Nam, the emissions of GHGs are not well quantified, in particular from the MSW management system. In this study, we estimated emissions of GHGs from the MSW management system of Ho Chi Minh City (HCMC), considering the current waste management practices. In HCMC, landfilling has been a common practice of solid waste management. About 85 percent of the total MSW generated in the city has been landfilled at two landfill sites. Our estimates show that landfilling was the significant source of GHGs in HCMC, with a net contribution of 781.05 kg CO2-equivalent (CO2-eq.) per tonne of MSW landfilled. From the whole MSW management system, the direct GHG emission was 768.61 (kg CO2-eq. per tonne of MSW) with avoided emissions of 72.47 (kg CO2-eq. per tonne of MSW) through composting and recycling of MSW. The net GHG emission from the MSW management system was 696.14 kg CO2-eq. per tonne of MSW (≈1.665 million tonnes of CO2-eq. per year). The GHG emission data of this study may be useful to policymakers for making effective climate change mitigation policies.
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Zeng, Lin, Tie Mao Shi, and Yuan Man Hu. "A Quantitative Research on Carbon Emissions in the Residential Area of China Based on LCP Theory." Applied Mechanics and Materials 587-589 (July 2014): 536–40. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.536.
Abstract:
As the residential area is the basic functional unit in the city, its number is large and its construction project is huge; accordingly, the CO2 emission is also huge in the process of construction and use. On the basis of the LCP theory and method, the researchers in this paper propose a new approach used to calculate the carbon emissions in the urban residential area through comprehensively considering the CO2 emission and CO2 absorption of carbon sink-green space in the total life cycle of the urban community. In addition, taking the typical multi-story residential areas in Shenyang City as the sample, the researchers calculate the carbon emission and discuss the features of emission in the residential area as well as the method and potential of reducing the carbon emission. The calculation results show that, the carbon emissions in the process of operation an use account for the largest proportion for the total life cycle, up to 83.8%; the carbon emissions in the process of preparing the materials for construction account for 7.69%; the carbon emissions at the stage of building demolition account for 5.32%. The carbon emissions at the stage of construction are the smallest in amount, which can be basically negligible. According to the existing energy structure, construction specifications and technical level, 4.8% of the CO2 emissions in the residential area can be absorbed through the green space and that the carbon emissions in the residential area can be reduced through taking the energy conservation measures, using the renewable energy and increasing the area of carbon sinks.
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Indriyani, Lies, La Gandri, Jois Liling Padang, and Sahindomi Bana. "Carbon Footprint Analysis of Household Activities and CO2 Reduction Efforts in Pondambea Village, Kadia District, Kendari City." Journal of Soilscape and Agriculture 1, no. 1 (September 5, 2022): 15–21. http://dx.doi.org/10.19184/jsa.v1i1.124.
Abstract:
The increase in population causes an effect on increasing CO2 production, especially from the household energy sector. The increase in the concentration of CO2 in the atmosphere is the main trigger for climate change and the effects of greenhouse gases. Indications of the occurrence of this phenomenon can be seen from the increase in air temperature and the formation of an urban heat island in Kendari City in the last 10 years. This study aims to determine the amount of CO₂ emissions from household activities and the absorption of CO2 gas from tree species in Pondambea Village, Kadia District, Kendari City. The method used is a quantitative technique to calculate primary and secondary CO2 emissions. The results show that the total CO2 emission in Pondambea Village is 424.22 tons/month. Meanwhile, the carbon absorption capacity of tree species in Pondambea Village is 421.15 tons/month, so that the remaining carbon emissions are 3.07 tons/month. Therefore, to maintain emission absorption and create zero emission in Pondambea Village, this study recommends maintaining the number of existing trees and adding at least 6 glodokan pole trees or at least 5 king palm trees
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Suryati, I., A. Hijriani, and I. Indrawan. "Estimation of greenhouse gas emission from household activities during the COVID-19 pandemic in Binjai City, North Sumatera." IOP Conference Series: Earth and Environmental Science 896, no. 1 (November 1, 2021): 012054. http://dx.doi.org/10.1088/1755-1315/896/1/012054.
Abstract:
Abstract Household activities have the potential to produce greenhouse gas emissions. The government’s policy to work and study from home during the COVID-19 pandemic affects greenhouse gas emissions produced by household activities, starting from energy and waste and liquid waste produced, so it is necessary to carry out an emission inventory. The purpose of this study is to calculate greenhouse gas emissions (CO2 and CH4) from household activities in Binjai City during the COVID-19 pandemic and determine emission reduction scenarios that can be carried out in Binjai City. The calculation method used is based on the 2006 IPCC (Intergovernmental Panel in Climate Change) guidelines. CO2 emissions resulting from the use of LPG are 2025.80 tons CO2e/month, the use of fuel for daily transportation activities is 3484.84 tons CO2e/month, and electricity usage is 14956.66 Ton CO2e/month. CH4 emissions produced from domestic liquid waste are 417.14 tons CO2e/month, and household waste is 27.54 tons CO2e/month. The COVID-19 pandemic increases GHG emissions from household electricity consumption in Binjai City by ± 7% and reduces GHG emissions from fuel consumption by 3.5%.
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Huang, Xianghua, Shidong Chen, Decheng Xiong, Chao Xu, and Zhijie Yang. "Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City." Computational Intelligence and Neuroscience 2022 (August 8, 2022): 1–14. http://dx.doi.org/10.1155/2022/7546742.
Abstract:
Global warming has become the focus of attention of the international community, and the control of carbon dioxide emissions has become one of the necessary choices for the development strategies of countries around the world. Cities are places where carbon dioxide emissions are concentrated. The key to controlling carbon emissions is to control the carbon emissions of cities. My country is currently in the process of rapid urbanization. Quantitative studies of the carbon cycle at the city level will help to take stock of carbon dioxide emissions in cities. On the other hand, it is helpful to understand the status and role of the urban carbon cycle in the process of the regional carbon cycle. Through the analysis and prediction of the elements influencing the carbon cycle of smart cities, this paper first determines the factors affecting smart cities in the carbon cycle process as industrial carbon emission strength factors, industrial structure effects, economic development factors, and population elements. It is found that the major positive factors affecting the significant add of CO2 emissions in smart cities from 2010 to 2019 are economic development factors and demographic factors, including economic development factors GDP/per capita GDP. The per capita contribution to CO2 emissions is higher than the model established by adjusting the affecting elements of overall CO2 emissions, except that the proportion of economic development factors in total CO2 emissions from 2013 to 2015 was lower than the increase in total CO2 emissions. The comparison can better reflect the relation between CO2 emissions and influencing elements. The main determinants affecting CO2 emissions are the expansion of the financial condition, the increase in the average daily population, and the increase in construction work. The adaptation index is judged to be consistent, indicating that the model adjustment effect is good; finally, the green computing in the smart city predicts the carbon cycle process, and the actual value trend line and the predicted value trend line are not much different from the practical value, the forecast error is small, and the prediction results are credible. Global warming has become the focus of attention of the international community, and carbon emission control has become one of the necessary options in the development strategies of countries around the world. Cities are the places where carbon emissions are concentrated. The key to controlling carbon emissions is to control urban carbon emissions. At present, my country is in the process of rapid urbanization. Quantitative research on the carbon cycle at the city level will help to establish an inventory accounting of urban carbon emissions. On the other hand, it is convenient to deeply understand the status and role of the urban carbon cycle in the process of the regional carbon cycle.
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Zhang, Qianqian, K. Folkert Boersma, Bin Zhao, Henk Eskes, Cuihong Chen, Haotian Zheng, and Xingying Zhang. "Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2." Atmospheric Chemistry and Physics 23, no. 1 (January 13, 2023): 551–63. http://dx.doi.org/10.5194/acp-23-551-2023.
Abstract:
Abstract. Quantification and control of NOx and CO2 emissions are essential across the world to limit adverse climate change and improve air quality. We present a new top-down method, an improved superposition column model to estimate day-to-day NOx and CO2 emissions from the large city of Wuhan, China, located in a polluted background. The latest released version 2.3.1 TROPOMI (TROPOspheric Monitoring Instrument) NO2 columns and version 10r of the Orbiting Carbon Observatory-2 (OCO-2)-observed CO2 mixing ratio are employed. We quantified daily NOx and CO2 emissions from Wuhan between September 2019 and October 2020 with an uncertainty of 31 % and 43 %, compared to 39 % and 49 % with the earlier v1.3 TROPOMI data, respectively. Our estimated NOx and CO2 emissions are verified against bottom-up inventories with minor deviations (<3 % for the 2019 mean, ranging from −20 % to 48 % on a daily basis). Based on the estimated CO2 emissions, we also predicted daily CO2 column mixing ratio enhancements, which match well with OCO-2 observations (<5 % bias, within ±0.3 ppm). We capture the day-to-day variation of NOx and CO2 emissions from Wuhan in 2019–2020, which does not reveal a substantial “weekend reduction” but does show a clear “holiday reduction” in the NOx and CO2 emissions. Our method also quantifies the abrupt decrease and slow NOx and CO2 emissions rebound due to the Wuhan lockdown in early 2020. This work demonstrates the improved superposition model to be a promising new tool for the quantification of city NOx and CO2 emissions, allowing policymakers to gain real-time information on spatial–temporal emission patterns and the effectiveness of carbon and nitrogen regulation in urban environments.
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Pillai, Dhanyalekshmi, Michael Buchwitz, Christoph Gerbig, Thomas Koch, Maximilian Reuter, Heinrich Bovensmann, Julia Marshall, and John P. Burrows. "Tracking city CO<sub>2</sub> emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany." Atmospheric Chemistry and Physics 16, no. 15 (August 2, 2016): 9591–610. http://dx.doi.org/10.5194/acp-16-9591-2016.
Abstract:
Abstract. Currently, 52 % of the world's population resides in urban areas and as a consequence, approximately 70 % of fossil fuel emissions of CO2 arise from cities. This fact, in combination with large uncertainties associated with quantifying urban emissions due to lack of appropriate measurements, makes it crucial to obtain new measurements useful to identify and quantify urban emissions. This is required, for example, for the assessment of emission mitigation strategies and their effectiveness. Here, we investigate the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat) which was proposed to the European Space Agency (ESA) to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of CO2 fluxes, and atmospheric transport. To achieve this, we use (i) a high-resolution modelling framework consisting of the Weather Research Forecasting model with a greenhouse gas module (WRF-GHG), which is used to simulate the atmospheric observations of column-averaged CO2 dry air mole fractions (XCO2), and (ii) a Bayesian inversion method to derive anthropogenic CO2 emissions and their errors from the CarbonSat XCO2 observations. We focus our analysis on Berlin, Germany using CarbonSat's cloud-free overpasses for 1 reference year. The dense (wide swath) CarbonSat simulated observations with high spatial resolution (approximately 2 km × 2 km) permits one to map the city CO2 emission plume with a peak enhancement of typically 0.8–1.35 ppm relative to the background. By performing a Bayesian inversion, it is shown that the random error (RE) of the retrieved Berlin CO2 emission for a single overpass is typically less than 8–10 Mt CO2 yr−1 (about 15–20 % of the total city emission). The range of systematic errors (SEs) of the retrieved fluxes due to various sources of error (measurement, modelling, and inventories) is also quantified. Depending on the assumptions made, the SE is less than about 6–10 Mt CO2 yr−1 for most cases. We find that in particular systematic modelling-related errors can be quite high during the summer months due to substantial XCO2 variations caused by biogenic CO2 fluxes at and around the target region. When making the extreme worst-case assumption that biospheric XCO2 variations cannot be modelled at all (which is overly pessimistic), the SE of the retrieved emission is found to be larger than 10 Mt CO2 yr−1 for about half of the sufficiently cloud-free overpasses, and for some of the overpasses we found that SE may even be on the order of magnitude of the anthropogenic emission. This indicates that biogenic XCO2 variations cannot be neglected but must be considered during forward and/or inverse modelling. Overall, we conclude that a satellite mission such as CarbonSat has high potential to obtain city-scale CO2 emissions as needed to enhance our current understanding of anthropogenic carbon fluxes, and that CarbonSat-like satellites should be an important component of a future global carbon emission monitoring system.
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Sun, Li, Xianglai Mao, Lan Feng, Ming Zhang, Xuan Gui, and Xiaojun Wu. "Investigating the Direct and Spillover Effects of Urbanization on Energy-Related Carbon Dioxide Emissions in China Using Nighttime Light Data." Remote Sensing 15, no. 16 (August 20, 2023): 4093. http://dx.doi.org/10.3390/rs15164093.
Abstract:
Cities are the main emission sources of the CO2 produced by energy use around the globe and have a great impact on the variation of climate. Although the implications of urbanization and socioeconomic elements for carbon emission have been extensively explored, previous studies have mostly focused on developed cities, and there is a lack of research into naturally related elements due to the limited data. At present, remote sensing data provide favorable conditions for the study of large-scale and long-time series. Also, the spillover mechanism of urbanization effects on the discharge of carbon has not been fully studied. Therefore, it is necessary to distinguish the types of influence that various urbanization factors have on emissions of CO2. Firstly, this study quantifies the urban CO2 emissions in China by utilizing nighttime lighting images. Then, the spatio-temporal variations and spatial dependence modes of CO2 emissions are explored for 284 cities in China from 2000–2018. Finally, the study further ascertains that multi-dimensional urbanization, socio-economic and climate variables affect the discharge of carbon using spatial regression models. The results indicate that CO2 emissions have a remarkable positive spatial autocorrelation. Urbanization significantly increases CO2 emissions, of which the land urbanization contribution towards CO2 emissions is the most important in terms of spillover effects. Specifically, the data on urbanization’s direct effects reveal that CO2 emissions will increase 0.066%when the urbanization level of a city rises 1%, while the spillover effect indicates that an 0.492% emissions increase is associated with a 1% rise of bordering cities’ average urbanization level. As for the socio-economic factors, population density suppresses CO2 emissions, while technological levels boost CO2 emissions. The natural control factors effect a remarkable impact on CO2 emissions by adjusting energy consumption. This study can provide evidence for regional joint prevention in urban energy conservation, emission reduction, and climate change mitigation.
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Nuarsa, I. Wayan, Abd Rahman As-syakur, I. Gusti Alit Gunadi, and I. Made Sukewijaya. "Integrasi Teknologi Pengideraan Jauh dan Sistem Informasi Geografis untuk Estimasi Serapan dan Emisi CO2 di Kota Denpasar." ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) 12, no. 2 (November 30, 2018): 240. http://dx.doi.org/10.24843/ejes.2018.v12.i02.p12.
Abstract:
Integration of Remote Sensing Technology And Geographic Information Systems for Estimation of CO2 Updake and Emissions in Denpasar City
Rapid economic growth in the Denpasar City has an impact on the rate of population growth. This will lead to increasing land requirements for settlements, infrastructure, and other supporting facilities. Meanwhile, the availability of land for green open space (RTH) will decrease. Several studies show that from year to year the area of ??vegetation cover decreases, and the air temperature in Denpasar City is increasing. Therefore, research to calculate CO2 uptake by urban plants and CO2 emissions from various activities in the city of Denpasar is needed to be done. Estimates of CO2 uptake by plants are carried out using remote sensing technology and GIS. Meanwhile, the calculation of CO2 emissions is carried out by an inventory of CO2 pollutant sources from point sources, areas sources, and mobile sources. The output of this study is a distribution map of CO2 absorption and emissions. From the map it can be seen whether the CO2 emissions of Denpasar City are higher than the ability of existing plants to absorb them.
The results showed that the ability of plants in Denpasar as a green open space to absorb CO2 was 235,780.63 tCO2/year, while total emissions from pollutant sources were 862,955,856 tCO2/year. The sources of CO2 emissions include from point source 37,649 tons/year, from source area 95,310 tons/year, and from mobile sources at 862,955,856 tons/year. From the movable source the biggest contributor to CO2 emissions is light vehicles, which amounted to 540,355.88 tons/year (62.63%), then followed by motorcycles at 260,187.43 tons/year (30.16%). The amount of CO2 emissions in Denpasar City is 3.66 times greater than the ability of plants to absorb CO2 in 2015 and there is a tendency for this gap to be even greater in the future.
To overcome this problem, regulations are needed such as reducing the number of motorized vehicles by increasing public transportation services. The use of vehicles using energy sources other than fuel such as electricity is another alternative to consider. Finally, the increase in the number and quality of green open spaces is a conventional method that needs to be done.
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Wu, L., G. Broquet, P. Ciais, V. Bellassen, F. Vogel, F. Chevallier, I. Xueref-Remy, and Y. Wang. "Atmospheric inversion for cost effective quantification of city CO<sub>2</sub> emissions." Atmospheric Chemistry and Physics Discussions 15, no. 21 (November 5, 2015): 30693–756. http://dx.doi.org/10.5194/acpd-15-30693-2015.
Abstract:
Abstract. Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44 % of global energy-related CO2, and are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25 m a.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (~ 12 million inhabitants and 11.4 Tg C emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5 % (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by ~ 42 % but still corresponds to an annual uncertainty that is two times larger than the target of 5 %. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32 % for commercial and residential buildings, by 33 % for road transport and by 18 % for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15 % 2-sigma annual uncertainty for dispersed building emissions, and 18 % for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus deliver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments).
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Wang, Junbo, Liu Chen, Lu Chen, Xiaohui Zhao, Minxi Wang, Yiyi Ju, and Li Xin. "City-Level Features of Energy Footprints and Carbon Dioxide Emissions in Sichuan Province of China." Energies 12, no. 10 (May 27, 2019): 2025. http://dx.doi.org/10.3390/en12102025.
Abstract:
The sustainable development of the western region of China has always been essential to the national development strategy. The Western region has undertaken an industrial transfer from the Eastern and Central regions. Therefore, the CO2 emission intensity in the western region is higher than those of the Eastern and Central regions of China, and consequently its low-carbon development pathway has an important impact for China as a whole. Sichuan Province is not only the province with the highest CO2 emissions, but also the most economically developed province in Western China in 2018. In order to promote low carbon development in the western region, it is important to understand the features of emissions in Sichuan Province and to formulate effective energy strategies accordingly. This paper uses the IPCC regional emission accounting method to calculate the carbon emissions of 15 cities in Sichuan province, and to comply with the city-level emission accounts. The results show that the total carbon emissions of Sichuan province over the past 10 years was 3258.32 mt and reached a peak in 2012. The smelting and pressing of ferrous metals, coal mining and dressing were the leading sectors that contributed to the emissions, accounting for 17.86% and 15.82%, respectively. Raw coal, cleaned coal, and coke were the most significant contributors to CO2 emissions, accounting for 43.73%, 9.55%, and 6.60%, respectively. Following the above results, the Sichuan provincial government can formulate differentiated energy structure policies according to different energy consumption structures and carbon emission levels in the 15 cities. By controlling the level of total emissions and regulating larger industrial emitters in Sichuan province, some useful information could be provided as an essential reference for low-carbon development in Western China, and contribute to the promotion of emissions mitigation from a more holistic perspective.
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Wang, Huihui, and Weihua Zeng. "Revealing Urban Carbon Dioxide (CO2) Emission Characteristics and Influencing Mechanisms from the Perspective of Commuting." Sustainability 11, no. 2 (January 14, 2019): 385. http://dx.doi.org/10.3390/su11020385.
Abstract:
Commuting to and from work is one of the most important and regular routines using urban transport, being a major source for an increase in transport-related carbon dioxide (CO2) emissions. In this study, we explore the characteristics of CO2 emissions from commuter travel in Beijing from different perspectives. A bottom-up approach from a macro perspective is used to analyze recent changing trends of carbon emissions due to commuter travel modes in Beijing, and to identify the main sources of carbon emission increases that affect transportation. To identify CO2 emission characteristics and influencing mechanisms in Beijing, the proportion of commuting modes, commuting distance, and commuting-related CO2 emissions by Ring Roads was analyzed. The commuting-related CO2 emission model, based on Tobit models from the microscopic perspective, was constructed to explore the main factors affecting CO2 emissions of individuals/households. Results show that CO2 emissions due to commuting in Beijing in recent years has presented an increasing trend. In 2014, the amount of CO2 emissions from commuters had already reached the level of 553.68 × 104 t, with CO2 emissions generated by car trips accounting for 75–80% of emissions. Average individual/household commuting-related CO2 emissions on the Ring Road inside the main urban areas of Beijing shows a gradual increasing trend, with the growth trends between the 3rd–5th Ring Road being the largest. Household locations separated by Ring Roads and the occupation type of residents are important factors affecting CO2 emissions. Commuters with access to a car, those having a higher income, and those located in the outer regions of the main urban areas produce more CO2 emissions. To reduce the increasing trend of CO2 emissions in Beijing, it is important that the government accelerates the development of public transport, industry, and residential facilities along the outskirts of the city, along the Ring Road, and along the radix road.
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Liu, Luyun, Lingling Xun, Zhiyuan Wang, Huaiwan Liu, Yu Huang, and Komi Bernard Bedra. "Peak Carbon Dioxide Emissions Strategy Based on the Gray Model between Carbon Emissions and Urban Spatial Expansion for a Built-Up Area." Applied Sciences 13, no. 1 (December 23, 2022): 187. http://dx.doi.org/10.3390/app13010187.
Abstract:
Urban spatial expansion affects almost every dimension of sustainable urban development. A good grasp of the relationship between urban spatial evolution and carbon emissions can be the key to urban spatial governance. As a central city in the central region and a national low-carbon pilot city, Changsha has experienced a rapid expansion of construction land and growing carbon emissions. In this paper, four variable factors and five variable factors of carbon emission were used for the case city Changsha in 1979, 1996, 2003, 2008, 2013 and 2016. Based on the “double carbon” constraint target, the total carbon emissions, carbon-emission intensity and per capita carbon emission constraint indices were forecasted until 2030. They are 87.29 million t-CO2, 0.45 t-CO2/CNY104 and 8.73 t-CO2/person, respectively. The scale of urban land is controlled at 889.61; the constraint indices of residential, commercial service land, industrial land and road square land scales are 231.3 km2, 143.88 km2, 150.17 km2 and 135.83 km2, respectively. The land expansion intensity, urban compactness and shortest travel distance constraint indices are 6.19, 0.236 and 96,086.76 km, respectively. The results of this analysis can provide scientific guidance for the next step in territorial spatial master planning and low-carbon governance.
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Hosseingholizadeh, M., V. Coors, H. Ostadabbas, and F. Friesecke. "DEVELOPMENT OF QGIS PLUGIN FOR URBAN ENERGY SIMULATION USING 3D CITY MODEL AT THE CITY DISTRICT LEVEL." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023 (December 5, 2023): 81–90. http://dx.doi.org/10.5194/isprs-annals-x-1-w1-2023-81-2023.
Abstract:
Abstract. In the context of climate change, the increasing demand for energy-efficient buildings and sustainable urban development has become a pressing issue due to the significant proportion of global energy consumption and carbon dioxide (CO2) emissions attributable to the building sector. This requires a concerted effort to reduce its environmental impact, and Geographic Information System (GIS) applications are vital tools for achieving this by optimizing heat supply, calculating costs, analyzing profitability, and balancing CO2 emissions. This study aims to address the challenge of achieving energy efficiency and reducing CO2 emissions in the building sector, specifically at the district level. To this end, the research objective is to develop a QGIS plugin that can simulate urban energy demand at the district level by integrating 2D data with CityGML files and connecting QGIS to SimStadt software via API to visualize the simulated urban energy results in 3D on the Web Globe. The proposed plugin leverages the open-source QGIS tool QField to capture building conditions and connect 2D and 3D data on urban energy simulation. Supplementary to this, this plugin provides up-to-date information on energy demand, consumption, CO2 emissions, building component conditions via updating related tables in the database. Decision-makers can use this comprehensive and user-friendly tool to understand and act on the results, ultimately leading to a CO2-neutral district by 2045. The development of the QGIS plugin represents a significant step towards sustainable urban development and climate change mitigation by utilizing GIS applications for optimizing energy demand and reducing CO2 emissions in the built environment.
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Yusup, G. S. B., R. J. Melda, I. Maman, and J. Li. "Sustainable Low Carbon Urban Lighting Analysis: Case Study of Bandung City." Journal of Engineering Sciences 7, no. 1 (2020): H9—H18. http://dx.doi.org/10.21272/jes.2020.7(1).h2.
Abstract:
Nowadays, lighting technology is in the transition period from conventional lighting to LED, which more environmentally friendly due to free of harmful substances such as mercury, lead, or other hazardous chemicals and gases. This low light pollution because directional light is carefully distributed precisely to the intended location. Performance of the lights also brighter than other lights. This research measuring the reduction of CO2 gas emissions before and after PJU (street lights) in Bandung is changed from the conventional to the LED, also mapping the CO2 gas emissions in six Development Areas (SWK). The basis for this research approach is a case study with before and after comparison, meaning that this approach only applies to one object that is the same as comparing the condition of the object before and after the treatment. In this study, the evaluation research method used is a causal method, which is a method that is more directed at impact evaluation research. Scientifically and objectively, PJU LED provides low CO2 emissions gas by up to 26 % in Bandung city. Keywords: CO2 emission, the light emitted diode (LED), street lights.
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Lou, Di Ming, Si Li Qian, Zhi Yuan Hu, and Pi Qiang Tan. "On-Road Gaseous Emission Characteristics of China IV CNG Bus in Shanghai." Advanced Materials Research 690-693 (May 2013): 1864–71. http://dx.doi.org/10.4028/www.scientific.net/amr.690-693.1864.
Abstract:
In this paper, on-road CO, THC, NOX, CO2 gaseous emissions characteristics of china IV CNG bus were analyzed based on on-road vehicle emission test in the peak and non-peak hours of city traffic in Shanghai using a portable emission measurement system (PEMS). The experimental results reveal that: compared with the condition results in the non-peak hours, it (conditions in the peak hours) have lower average speed, longer idle time and shorter high speed time; the NOX emission factor and rate in the peak hour reduced by 5.66% and 70.2%; the CO, HC, CO2 emissions factors are increased by 47.2%, 32.6%, 20.8%, and the CO, HC, CO2 emissions rates reduced by 1.94%, 26.5%, 48.7% respectively, compared with that in the non-peak hours; The CO, HC, NOX, CO2 emissions factors all decreased as bus speed increased, while they increased as bus acceleration increased; the gaseous emissions rates all increased as bus speed increased; both the emissions factors and emissions rates contributions are highest at accelerations, higher at cruise speeds, and the lowest at decelerations for non-idling buses; the emissions rates under the condition of idling is lowest; gaseous emissions contribution under the various operating conditions has displayed certain correlations with the percentage of the time for different operating conditions.
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Mao, Feng, Zhiheng Li, and Kai Zhang. "A Comparison of Carbon Dioxide Emissions between Battery Electric Buses and Conventional Diesel Buses." Sustainability 13, no. 9 (May 6, 2021): 5170. http://dx.doi.org/10.3390/su13095170.
Abstract:
To prove the important role of battery electric buses (BEBs) in reducing carbon dioxide (CO2) emissions, we propose a framework to compare CO2 emissions between BEBs and conventional diesel buses (CDBs) based on low sampling frequency BEBs data at the city scale in Shenzhen. We applied the VT-Micro model to improve the estimation of CDBs’ CO2 emissions. A modal-activity-based method was implemented to reconstruct the second-by-second trajectories from the dataset as the input of the VT-Micro model. We updated the data of the Guangdong power generation mix to improve the estimation of BEBs’ CO2 emissions. The experiments showed that BEBs could reduce CO2 emissions by 18.0–23.9% in comparison with CDBs when the frequency of air-conditioning usage was low. In addition, BEBs tended to achieve more CO2 emission reduction benefits when the transit buses traveled at a low speed. Improving the traffic efficiency of road networks and promoting inter-provincial electricity trading are important to promote the adoption of BEBs.
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Ma, Zhongxin, and Fenglan Wu. "Smart City, Digitalization and CO2 Emissions: Evidence from 353 Cities in China." Sustainability 15, no. 1 (December 23, 2022): 225. http://dx.doi.org/10.3390/su15010225.
Abstract:
The development of digital technology provides new governance methods for achieving the goal of “carbon peaking and carbon neutrality”. Since 2013, the pilot construction of smart cities in China has strengthened the government’s digital governance capabilities and significantly influenced the reduction in carbon emissions. This paper provides empirical evidence for the driving effect of digitization on carbon emission reduction based on panel data from 353 cities in China. The results show that digital governance based on smart city construction pilots has significantly reduced regional carbon emissions, and the implementation of smart city construction pilots has reduced regional carbon emissions by an average of 6.6%, and this effect is sustainable over the long term. The increase in the level of digitalization has significantly promoted carbon emission reduction. From the perspective of the impact path, regional green patent innovation has played a significant partial intermediary effect in the process of digitization-driven carbon emission reduction. From a micro-mechanism standpoint, digitization plays a significant role in promoting the green innovation of high-polluting listed companies.
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Mitchell, Logan E., John C. Lin, David R. Bowling, Diane E. Pataki, Courtenay Strong, Andrew J. Schauer, Ryan Bares, et al. "Long-term urban carbon dioxide observations reveal spatial and temporal dynamics related to urban characteristics and growth." Proceedings of the National Academy of Sciences 115, no. 12 (March 5, 2018): 2912–17. http://dx.doi.org/10.1073/pnas.1702393115.
Abstract:
Cities are concentrated areas of CO2 emissions and have become the foci of policies for mitigation actions. However, atmospheric measurement networks suitable for evaluating urban emissions over time are scarce. Here we present a unique long-term (decadal) record of CO2 mole fractions from five sites across Utah’s metropolitan Salt Lake Valley. We examine “excess” CO2 above background conditions resulting from local emissions and meteorological conditions. We ascribe CO2 trends to changes in emissions, since we did not find long-term trends in atmospheric mixing proxies. Three contrasting CO2 trends emerged across urban types: negative trends at a residential-industrial site, positive trends at a site surrounded by rapid suburban growth, and relatively constant CO2 over time at multiple sites in the established, residential, and commercial urban core. Analysis of population within the atmospheric footprints of the different sites reveals approximately equal increases in population influencing the observed CO2, implying a nonlinear relationship with CO2 emissions: Population growth in rural areas that experienced suburban development was associated with increasing emissions while population growth in the developed urban core was associated with stable emissions. Four state-of-the-art global-scale emission inventories also have a nonlinear relationship with population density across the city; however, in contrast to our observations, they all have nearly constant emissions over time. Our results indicate that decadal scale changes in urban CO2 emissions are detectable through monitoring networks and constitute a valuable approach to evaluate emission inventories and studies of urban carbon cycles.
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Chen, Qiu, Haoran Yang, Wenguo Wang, and Tianbiao Liu. "Beyond the City: Effects of Urbanization on Rural Residential Energy Intensity and CO2 Emissions." Sustainability 11, no. 8 (April 24, 2019): 2421. http://dx.doi.org/10.3390/su11082421.
Abstract:
Trends of rural residential energy consumption and CO2 emission should be evaluated in a broader context of urbanization, especially in developing countries where urbanization is in its expanding stage. In this study, we use the STIRPAT model and various panel regression techniques to explore the impact of urbanization on rural residential energy consumption and CO2 emission by using data from Southwest China. The results show that a higher urbanization level contributes to higher total residential energy intensity. Increases in net income per capita can decrease the intensities of traditional biomass energy and non-biomass energy, while industrialization has a negative effect only on non-biomass energy intensity. Land use change driven by urbanization can also lower the intensities of total residential energy, traditional biomass energy and non-biomass energy. Moreover, the impact of total residential energy intensity on emissions is positive. Particularly, traditional biomass energy accounts for most of CO2 emissions derived from the use of residential energy. As urbanization is expected to increase in the developing world and lead to more CO2 emissions from rural areas, policies which intend to reduce the intensity of traditional biomass energy, promote biogas and industrialization, and raise net income of rural residents can be used as effective mitigation strategies.
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Zhou, Zhi Hua, Zi Chao Tan, Guo Qiang Yang, and She Ming Qiu. "The Study on Community Energy Planning and Emission Reduction in China." Advanced Materials Research 433-440 (January 2012): 1442–46. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.1442.
Abstract:
Climate change is becoming a highlight of the world. As the world's second largest CO2 emission country, China faces increasing pressure. Energy consumption and utilizing is the major source of CO2 emissions. Optimization of the regional energy configuration can not only reduce energy consumption, but also reduce carbon dioxide emissions. Thus, it will achieve energy conservation and sustainable development. Based on the Eco-city constructed by China and Sino-Singapore, this paper calculates the regional energy-saving under the requirement of existing Energy Conservation Code, plans its energy saving quantity by taking some measurements and then predicts the carbon dioxide emission reductions. The result shows that using effective measures to save energy can reduce 227772t carbon dioxide emissions. Using renewable energy and energy saving measures will reduce 371414t CO2, which has a striking effect. So changing energy structure and using renew energy are main measures to reduce CO2 emission.
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Lian, Jinghui, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais. "Sensitivity to the sources of uncertainties in the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris." Atmospheric Chemistry and Physics 21, no. 13 (July 14, 2021): 10707–26. http://dx.doi.org/10.5194/acp-21-10707-2021.
Abstract:
Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of 1-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations, and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime model–data misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Nevertheless, our results demonstrate the potential of our optimal CO2 atmospheric modeling system to be utilized in atmospheric inversions of CO2 emissions over the Paris metropolitan area. We evaluated the model performances in terms of wind, vertical mixing, and CO2 model–data mismatches, and we developed a filtering algorithm for outliers due to local contamination and unfavorable meteorological conditions. Analysis of model–data misfit indicates that future inversions at the mesoscale should only use afternoon urban CO2 measurements in winter and suburban measurements in summer. Finally, we determined that errors related to CO2 boundary conditions can be overcome by including distant background observations to constrain the boundary inflow or by assimilating CO2 gradients of upwind–downwind stations rather than by assimilating absolute CO2 concentrations.
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Kinakh, V., T. Oda, R. Bun, and O. Novitska. "Mitigating geolocation errors in nighttime light satellite data and global CO2 emission gridded data." Mathematical Modeling and Computing 8, no. 2 (2021): 304–16. http://dx.doi.org/10.23939/mmc2021.02.304.
Abstract:
Accurate geospatial modeling of greenhouse gas (GHG) emissions is an essential part of the future of global GHG monitoring systems. Our previous work found a systematic displacement in the high-resolution carbon dioxide (CO2) emission raster data of the Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emission product. It turns out this displacement is due to geolocation bias in the Defense Meteorological Satellite Program (DMSP) nighttime lights (NTL) data products, which are used as a spatial emission proxy for estimating non-point source emissions distributions in ODIAC. Mitigating such geolocation error (~1.7 km), which is on the same order of the size of the carbon observing satellites field of view, is especially critical for the spatial analysis of emissions from cities. In this paper, there is proposed a method to mitigate the geolocation bias in DMSP NTL data that can be applied to DMSP NTL-based geospatial products, such as ODIAC. To identify and characterize the geolocation bias, we used the OpenStreetMap repository to define city boundaries for a large number of global cities. Assumption is that the total emissions within the city boundaries are at the maximum if there is no displacement (geolocation bias) in NTL data. Therefore, it is necessary to find an optimal vector (distance and angle) that maximizes the ODIAC total emissions within cities by shifting the emission fields. In the process of preparing annual composites of the nighttime stable lights data, some pixels of the DMSP data corresponding to water bodies were zeroed, which due to the geolocation bias unreasonably distorted the ODIAC emission fields. Hence, an original approach for restoring data in such pixels is considered using elimination of the factor that distorted the ODIAC emission fields. It is also proposed a bias correction method for shifted high-resolution emission fields in ODIAC. The bias correction was applied to multiple cities from the different continents. It is shown that the bias correction to the emission data (elimination of geolocation error in non-point emission source fields) increases the total CO2 emissions within city boundaries by 4.76% on average, due to reduced emissions from non-urban areas to which these emissions were likely to be erroneously attributed.