국내 일반공항에서 항공기에 의한 대기오염물질과 온실가스의 배출량 산정 및 특성 분석

Emissions of greenhouse gases and air pollutants from commercial aircraft at international airports in Korea

Emissions of air pollutants and greenhouse gases (GHGs) by aircraft at the Gimhae International Airport (GIA) were investigated using the Emissions and Dispersion Modeling System (EDMS) version 5.1.3. The number of Landing and Take-Off (LTO) at the GIA for aircraft B737 was dominant, accounting for more than 60% of the total LTOs. For air pollutant emissions, CO was the most dominant pollutant by aircraft, followed by , VOCs, , etc. The emissions of CO, , and VOCs in 2009 (and 2010) at the GIA were 974 (968), 447 (433), 118 (122) ton/yr, respectively. The emissions of GHGs such as , , and in 2009 (and 2010) were 110,795 (111,114), -0.157 (-0.151), and 1,989 (1,998) ton/yr, respectively. The negative number in emission represents the consumption of atmospheric in the engine. In addition, the emissions of most air pollutants (except for ) and GHGs were estimated to be high in Taxi-Out and Climb-Out modes.

BackgroundAir pollution in China has raised great concerns due to its adverse effects on air quality, human health, and climate. Emissions of air pollutants (APs) are inherently linked with CO2 emissions through fossil-energy consumption. Knowledge of the characteristics of APs and CO2 emissions and their relationships is fundamentally important in the pursuit of co-benefits in addressing air quality and climate issues in China. However, the linkages and interactions between APs and CO2 in China are not well understood.ResultsHere, we conducted an ensemble study of six bottom-up inventories to identify the underlying drivers of APs and CO2 emissions growth and to explore their linkages in China. The results showed that, during 1980–2015, the power and industry sectors contributed 61–79% to China’s overall emissions of CO2, NOx, and SO2. In addition, the residential and industrial sectors were large emitters (77–85%) of PM10, PM2.5, CO, BC, and OC. The emissions of CH4, N2O and NH3 were dominated by the agriculture sector (46–82%) during 1980–2015, while the share of CH4 emissions in the energy sector increased since 2010. During 1980–2015, APs and greenhouse gases (GHGs) emissions from residential sources generally decreased over time, while the transportation sector increased its impact on recent emissions, particularly for NOx and NMVOC. Since implementation of stringent pollution control measures and accompanying technological improvements in 2013, China has effectively limited pollution emissions (e.g., growth rates of –10% per year for PM and –20% for SO2) and slowed down the increasing trend of carbon emissions from the power and industrial sectors. We also found that areas with high emissions of CO, NOx, NMVOC, and SO2 also emitted large amounts of CO2, which demonstrates the possible common sources of APs and GHGs. Moreover, we found significant correlations between CO2 and APs (e.g., NOx, CO, SO2, and PM) emissions in the top 5% high-emitting grid cells, with more than 60% common grid cells during 2010–2015.ConclusionsWe found significant correlation in spatial and temporal aspects for CO2, and NOx, CO, SO2, and PM emissions in China. We targeted sectorial and spatial APs and GHGs emission hot-spots, which help for management and policy-making of collaborative reductions of them. This comprehensive analysis over 6 datasets improves our understanding of APs and GHGs emissions in China during the period of rapid industrialization from 1980 to 2015. This study helps elucidate the linkages between APs and CO2 from an integrated perspective, and provides insights for future synergistic emissions reduction.

Synergizing air pollution control and climate change mitigation has been of significant academic and policy concern. The synergy between air pollution and carbon emissions is one of the measures to understand the characteristics and process of the air pollution–carbon synergistic control, which will also provide valuable information for collaboratively achieving Sustainable Development Goals (SDGs) (such as SDGs 11 and 13). This study establishes a systematic framework integrating emissions inventory and projection models, correlation mining and typology analysis methods to predictively evaluate the synergy and comprehensive coordination between air pollution and carbon dioxide (CO2) emissions in Chinese cities by 2030, 2050, and 2060 under different policy scenarios for air pollution and CO2 emissions control. The results reveal the significant effects of synergistically implementing clean air and aggressive carbon-reducing policies on mitigating air pollution and CO2 emissions. Under the On-time Peak-Net Zero-Clean Air and Early Peak-Net Zero-Clean Air scenarios, the total reduction and synergy for air pollution and CO2 emissions will be more significant, particularly by 2050 and 2060. This study is the first to integrate scenario projection and synergy evaluation in air pollution and CO2 research, providing a novel supplement to the air pollution–climate change synergy methodology based on co-benefit estimation. The methods and findings will also contribute to measuring the achievement and analyzing the interaction of the SDGs.

Kupang city is growth rapidly and located in a strategic position between Australia and Timor Leste. A sharp increase of GHG emission along with environmental pollution, contamination of water, air and improper waste disposal practices as its consequence to the global environment. The city's government ambition to evaluate impact of economic activity on greenhouse gases (GHG) emission contribution. This paper outlined pollutant sectors that contribute substantially to GHG emission in Kupang along with its structure, and count an estimated amount of emission coefficients for 27 economy sectors. More in-depth explanation about indirect coefficient pollutant emission which beneficial not only for calculation of the emission amount but more as inventory data for LCA. The paper is investigated review the trends of some priority sectors, then introduction of indirect coefficients of pollutant sectors, and showed the Pollutant Emission Structure for Kupang. After that, an estimated amount of Kupang GHG emission under BAU is also counted and confirmed. The paper only considers GHG emission issues while air pollutant emission only be provided as inventory data but will not be used as exogenous data for this paper. In the final part a brief explanation and implications of GHG emission policy in Kupang are identified. A detailed of input-output data for individual process are provided includes all groups of processes or industry sectors relevant to economy activities in Kupang City. A time period for Global Warming Potential (GWP) 20 year and 100 years are used to forecasted amounts share of total GHG emission in Kupang and Indonesia by 2020 compared to 2010. As results first, the GHG emission and air pollutant coefficients for 27 sectors in Kupang based on method is presented in NIES which use to count the GHG emission. These also become an Inventory data for researchers of regional science in Indonesia, however, geography and socioeconomic conditions in every region is different, so that some criteria will be applied. Second, found total GHG emission in Kupang is $1.0164\mathrm{x} 10^{-3}$ Gt or around 0.047% compared to total GHG emission by 2010 and 0.034% compared to total GHG emission by 2020 in Indonesia. The study suggests to government consider a proper method in decide a reliable environmental policy and technical measures to reach GHG emission targets by 2020. Third, total share of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> e in Indonesia emitted from Kupang for GWP 20 years and 100 years respectively were came out as follow.

Currently, Tangshan confronts the dual challenge of elevated carbon emissions and substantial pollution discharge from the iron and steel industries (ISIs). While significant efforts have been made to mitigate air pollutants and carbon emissions within the ISIs, there remains a gap in comprehending the control of carbon emissions, air pollutant emissions, and their contributions to air pollutant concentrations at the enterprise level. In this study, we devised the Air Pollutant and Carbon Emission and Air Quality (ACEA) model to identify enterprises with noteworthy air pollution and carbon emissions, as well as substantial contributions to air pollutant concentrations. We constructed a detailed inventory of air pollutants and CO2 emissions from the iron and steel industry in Tangshan for the year 2019. The findings reveal that in 2019, Tangshan emitted 5.75 × 104 t of SO2, 13.47 × 104 t of NOx, 3.55 × 104 t of PM10, 1.80 × 104 t of PM2.5, 5.79 × 106 t of CO and 219.62 Mt of CO2. The ACEA model effectively pinpointed key links between ISI enterprises emitting air pollutants and carbon dioxide, notably in pre-iron-making processes (coking, sintering, pelletizing) and the Blast furnace. By utilizing the developed air pollutant emission inventory, the CALPUFF model assessed the impact of ISI enterprises on air quality in the Tangshan region. Subsequently, we graded the performance of air pollutant and CO2 emissions following established criteria. The ACEA model successfully identified eight enterprises with significant air pollution and carbon emissions, exerting notable influence on air pollutant concentrations. Furthermore, the ACEA outcomes offer the potential for enhancing regional air quality in Tangshan and provide a scientific instrument for mitigating air pollutants and carbon emissions. The effective application of the ACEA model in Tangshan’s steel industry holds promise for supporting carbon reduction initiatives and elevating environmental standards in other industrial cities across China.

Legislation to cap and trade greenhouse gas (GHG) emissions was approved by a 219-212 vote of the United States House of Representatives on June 26, 2009. Cap and trade policy articulated in the American Clean Energy and Security (ACES) act of 2009 regulates GHGs including carbon dioxide, methane, nitrous oxide, sulfur hexafluoride, hydrofluorocarbons, perfluorocarbons and nitrogen trifluoride. Debate over the ACES act focused heavily on economic issues contrasted against concerns about climate change1. However, discussion largely ignored the potential for cap and trade legislation to contribute to reductions in levels of other harmful air pollutants, such as sulfur dioxide, particulate matter, and ozone precursors that share emission sources with GHGs. Under the bill, domestic GHG emissions are to be capped at 2005 annual levels, and reduced to 17% of those marks by 20502. The bill provides for an initial round of pollution permits to be made available, some free, others at auction. Subsequently, these permits can be bought and sold in the open market by organizations such as utility companies and manufacturing firms. A key provision in the ACES act requires the president to impose tariffs on countries that do not implement similar regulations on GHG emissions. While other potentially viable legislation, such as a tax on carbon emissions, has been proposed3, the current cap and trade legislation is the first bill to pass in either the House or Senate. The greenhouse gases regulated under the ACES act do not generally pose serious direct health risks. For example, nitrous oxide is used in dental procedures, and carbon dioxide is an ingredient in carbonated beverages. Other GHGs, like nitrogen trifluoride and sulfur hexafluoride, are not harmful at their current concentration levels, but can be hazardous to persons working with them if safety precautions are not taken. Instead, substantial human health benefits from cap and trade legislation could potentially come from reductions in ambient levels of harmful pollutants, such as particulate matter and ozone, that share emissions sources with GHGs. For example, 94% of CO2 emissions in the US result from combustion of fossil fuels, with electricity generation and transportation alone comprising nearly 70%. These are also the leading source of sulfur dioxide, fine particles having diameter small than 2.5 micrometers (PM2.5), and precursors to ozone such as mono-nitrogen oxides (NOx)4. While the time scale for potential impacts of cap and trade legislation on climate change and related health benefits is likely decades or centuries, ancillary air pollution mitigation could have immediate health benefits. In two nationwide epidemiological studies, daily levels of ambient ozone and PM2.5 have been linked to increased risk of cardiovascular and respiratory mortality5 and to increased risk of emergency hospital admissions, especially for heart failure6, respectively. Estimates of the potential health benefits attributable to reductions in harmful air pollutants resulting from mitigation of GHG emissions, at the city, region and national, have been substantial7. While US cap and trade legislation would likely reduce domestic air pollution levels, two caveats deserve consideration. First, methods for reducing GHG emissions typically reduce air pollution levels, but not always. This problem can be highlighted using airplanes as an example8. Two methods to reduce CO2 emissions from airplanes are to decrease aircraft weight or increase engine combustion temperatures. The former reduces both GHG and air pollution emissions, whereas the later reduces GHG emissions at the cost of increasing precursors to ozone. In the broader context of energy production, it is likely cap and trade legislation would drive a shift away from fossil fuel combustion to sources such as solar technology that produce much less air pollution. However, the exact technology development path is still uncertain. A second problem is the potential for domestic cap and trade legislation to transfer US emissions to newly industrialized nations. Countries facing lower production costs associated with looser regulations on GHG emissions would have an economic advantage over manufacturing industries in the US. However, increased air pollution from new manufacturing could be a key public health issue for developing regions, such as China's Pearl River delta, where air pollution levels are already much higher than standards in the US9. The economic and physical systems that would be affected by cap and trade legislation are extremely complex, and impacts on air pollution will have to be considered in a broad context. For example, while the absence of tariffs would likely push manufacturing, air pollution and related negative health effects to developing regions, those regions might experience health benefits associated with increased per capita income. The discussion is similarly complex in the physical domain. For example, some air pollutants, such as sulfate particulate matter, can contribute to short term climate cooling. Though still somewhat unclear, there is an emerging debate over the possibility that air pollution mitigation could actually exacerbate global warming in the short term10. While it faces potentially significant opposition and alteration in the Senate, the cap and trade bill recently passed in the House has progressed further through Congress than any other similar legislation. There is tremendous potential for legislation regulating GHG emissions, via cap and trade or other strategies, to simultaneously decrease emissions of harmful air pollutants and reduce morbidity and mortality attributable to cardiovascular and respiratory illness. Such improvements in public health have been linked to economic benefits from recovered workforce productivity8, and add important support for progress on cap and trade legislation versus delayed action.

Asian countries are major contributors to global air pollution and greenhouse gas emissions, with transportation demand and emissions expected to increase. However, few studies have been performed to evaluate policies that could reduce transport-related emissions in the region. This study explores transport-related CO2 and air pollutant emissions in major Asian nations along with the impacts of transport, climate, and emission control policies using the Asia-Pacific Integrated Model (AIM)/Transport model. Our results show that by 2050, CO2 emissions in developing countries will be 1.4–4.7-fold greater than the levels in 2005, while most air pollutant emissions will show large reductions (mean annual reduction rates of 0.2% to 6.1%). Notably, implementation of transport, emission control, and carbon pricing policies would reduce CO2 emissions by up to 33% and other air pollutants by 43% to 72%, depending on the emission species. An emission control policy represents the strongest approach for short-term and mid-term reduction of air pollutants. A carbon pricing policy would lead to a direct reduction in CO2 emissions; more importantly, air pollutant emissions would also be effectively reduced. Shifting to public transportation in developing countries can also greatly influence emissions reductions. An increase in traffic speed shows relatively small effects, but can be meaningful in Japan.

The transportation sector has significantly contributed to greenhouse gas and air pollutant emissions. Consequently, there is an urgent need to investigate strategies to synergize the reduction in CO2 and pollutant emissions in this sector. Using panel data from 30 provinces in China over the period from 2005 to 2018, this study employs spatial econometric models and mediation effect models to investigate the synergistic effects of carbon markets and environmental regulations on carbon reduction and pollution control in the transportation sector, along with the underlying transmission mechanisms. The results are as follows: (1) Carbon markets can achieve synergistic reduction effects in both CO2 emissions and pollutant emissions, whereas environmental regulations can reduce pollutant emissions alone in the transportation sector. (2) The synergistic reduction effects of carbon markets and environmental regulations in the transportation sector exhibit regional heterogeneity. The central region can realize synergistic reductions, while the western and eastern regions may experience an increase in CO2 and pollutant emissions and cross-regional transfers. (3) Carbon markets can achieve synergistic reduction effects in the transportation sector by influencing the industrial structure at the provincial level, transportation supply and demand at the sectoral level, and green willingness at the individual level.

Co-benefits analysis on climate change and environmental effects of wind-power: A case study from Xinjiang, China

This study investigates the effect of energy consumption on greenhouse gas (GHG) emissions in 33 African countries from 1995–2017. It contributes to the literature by investigating the effect of disaggregated measures of energy consumption (coal, oil and other liquids, renewable energy, and electricity) on GHG emissions (CO2, N2O, CH4, and total GHG emissions) in Africa and identifies the transmission channels through which energy consumption affects GHG emissions. The system GMM is used in the study as it accounts for possible endogeneity and the potential correlation between the error term and the country fixed effects. The results show that coal consumption significantly increases CO2, CH4, and total GHG emissions and reduces N2O emissions. Oil consumption increases CO2 and total GHG emissions but reduces N2O and CH4 emissions. Renewable energy consumption reduces CO2 and CH4 emissions but increases N2O emissions. Finally, electricity consumption promotes CO2, N2O, CH4 and total GHG emissions in Africa. Further analyses show that foreign trade and economic growth are the channels through which oil consumption increases GHG emissions. The adverse effect of electricity is through urbanization. Renewable consumption could decrease GHG emissions through sustainable urbanization and trade policies. The findings suggest that countries should gradually reduce coal consumption and encourage renewable energy consumption, which has the lowest impact on the environment.

The members of the Cooperation Council for the Arab States of the Gulf have typically addressed water scarcity problems by building energy-intensive desalination plants. Few efforts have addressed water scarcity through metering, pricing, and other efficiency measures to reduce demand. This paper examines how decreased leakage in the water distribution system and decreased residential water use in Abu Dhabi, United Arab Emirates, could decrease air pollutant and greenhouse gas emissions from desalination plants. We developed a probabilistic model to predict the effects of water use reductions on pollutant emissions from Abu Dhabi's major independent water and power plants, which use a combination of multi-stage flash distillation and multi-effect distillation to produce fresh water from seawater drawn from the Arabian Gulf. We examine three categories of scenarios for reducing water use: increasing the price signal to residential users, instituting demand management programs among residential users, and reducing water loss in the distribution system. Our analysis suggests that water conservation price incentives could reduce air pollutant and greenhouse gas emissions by 1% to 5%, depending on assumptions about how households respond to the incentives. Demand-side management programs curbing per capita water use to levels typical of the Singapore or the UK would curb emissions by 10% or 11%, respectively. Reducing water loss during distribution from the current high level of 35% to 15% (similar to loss rates in other developed nations) could cut emissions by more than 3%. Overall, our analysis suggests that high per capita water use contributes to ambient air pollution and greenhouse gas emissions in Abu Dhabi.

Synergy and co-benefits of reducing CO2 and air pollutant emissions by promoting electric vehicles—A case of Shanghai

Addressing climate change and improving air quality are prominent tasks facing China’s ecological environment. The synergistic emission reduction in greenhouse gases (GHGs) and air pollutants has become an important task of environmental governance in different provinces. In this study, Hebei Province was taken as the research object. Firstly, the emission factors of GHGs (CO2, CH4, and NO2) and air pollutants (SO2, NOX, and smoke &amp; dust) in Hebei Province from 2011 to 2020 were calculated and analyzed. Seven socio-economic indicators were selected to analyze the trend during the study period. The Spearman rank correlation coefficient method was used to analyze the correlation between GHG and air pollutant emissions. Finally, the synergistic control effect coordinate system and the cross-elasticity coefficient of emission reduction were used to study the synergistic emission reduction effect of GHGs and air pollutants. The results showed that the total amount of GHG emissions fluctuated slightly from 2011 to 2020, and energy activities were the main source of total GHG emissions. The total emissions of air pollutants decreased year by year, and decreased by 71.13% in 2020 compared with 2011. During the study period, the emission synergy between smoke &amp; dust and GHG was better than that between SO2, NOX, and GHG. GHG and SO2, NOX, and smoke &amp; dust achieved synergistic emission reduction in most years, but the overall emission reduction synergy was poor.

In order to promote the precise governance of air pollution in the Yellow River Basin(YRB), it is of great significance to reveal the spatio-temporal patterns of urban air pollution in the basin and its spatial mismatch characteristics with air pollutant emissions. Based on spatial autocorrelation model and spatial mismatch model, this paper selected air pollution-related monitoring data from 69 cities in YRB from 2015 to 2020 as samples, and used ArcGIS, Stata, GeoDa and other softwares to analyze the spatio-temporal patterns of urban air pollution and its spatial mismatch characteristics with air pollutant emissions in YRB. The results showed that: (1) Temporally, the average annual Air Quality Index (AQI) values of cities in YRB ranged from 78.22 to 97.08 in 2015–2020, among which, the average annual AQI values of cities in the upper, middle and lower reaches of the basin decreased from 79.86, 89.23 and 122.14 in 2015 to 66.87,82.98 and 98.43 in 2020. (2) Spatially, there were obvious spatial differences in urban air pollution in YRB, and the AQI was roughly distributed in a geographical gradient of upper reaches < middle reaches < lower reaches, and there were significant spatial correlations in urban air pollution, mainly showing ‘high-high’ and ‘low-low’ aggregating characteristics. Among them, the lower reaches of YRB had formed a concentrated ‘high pollution zone’. (3) There was an obvious spatial mismatch between urban air pollution and air pollutant emissions in YRB, among which the spatial mismatch was obvious in cities such as Wuhai, Zibo, Shizuishan, Yangquan, Taiyuan, Datong, Jiyuan, Kaifeng, Puyang and Xi’an. (4) To improve the overall situation of air pollution in the cities of YRB, this paper proposed that the geographical gradient difference of air pollution in the upper, middle and lower reaches of YRB needs to be fully considered, following the principle of ‘focused treatment, gradual progress, enhanced prevention’, and according to the spatial mismatch characteristics of urban air pollution and air pollutant emissions, it is necessary to build a ‘differentiated’ governance strategy system for urban air pollution in the basin, which is ‘tailored to local conditions and categorized measures’.