Atmospheric Pollutant Emissions Research Articles

Second Generation Biofuel – An Alternate Source of Energy

The use of fossil fuels in the current situation has been increased. These fossil fuels do not come under the category of sustainable sources due to its depleting nature. Fossil fuels also pollutes the environment by increased emission of Greenhouse Gases (GHG). In order to produce an alternate renewable energy and to reduce the percentage of environmental pollution caused, many technologies like solar energy, tidal energy, wind energy etc. came into existence. But all these forms of energy can be produced in terms of electricity. To meet the increasing fuel demand, renewable biofuels came into the field where biomasses are utilized to produce biofuels. Second generation renewable biofuels are produced from conventional plant sources with higher oil content whose efficiency is determined by the amount of Green House Gases (GHG) emitted and the life cycle cost whether positive, neutral or negative. High yielding energy crops such as sugarcane, corn, switchgrass, wheat etc. are subjected to various processes / fermentation to yield biofuels like bioethanol, biobutanol, biohydrogen, biodiesel etc. The US and Brazil are replacing the demand for gasoline with around 15% of bioethanol and it has a higher octane rating, increased engine’s compression ratio, increased thermal efficiency and ultimately reduces atmospheric pollution emissions. In future biofuels will be recognized as alternative fuel in transportation, energy generation, heat producer, charging electronics, environmental friendly cleaners, cooking, lubricants, adhesives etc. This review provides a brief outline about the second generation biofuels which would serve as an alternative energy in the near future.

An assessment of China's industrial emission characteristics using satellite observations of XCO2, SO2, and NO2

An effective assessment of industrial emission characteristics is necessary to formulate appropriate emission reduction measures. However, regular and complete emission reports are not always available. Therefore, this study aims to use satellite observations of atmospheric pollutants to evaluate the intensity, efficiency, industrial composition, and energy composition of industrial carbon emissions. Taking China as the study area, first, the XCO2 enhancement (△XCO2) and co-located SO2 and NO2 corresponding to the industrial land area were extracted based on the satellite data of OCO-2 (Orbiting Carbon Observatory-2) and Aura OMI (Ozone Monitoring Instrument). Then, the relationship between atmospheric pollutant composition and industrial emission characteristics in different regions is analyzed. Finally, an estimation model based on atmospheric pollution characteristics is constructed, and the characteristics of China's industrial emissions in 2015 are evaluated. Results show that evaluating the specific emission characteristics is possible by using the comprehensive satellite observations of atmospheric pollutants, and the estimation results are in good agreement with the sectoral emission inventory. High NO2 and high emission intensity are mainly distributed in eastern China, while high SO2 and low emission efficiency are mainly distributed in the north. Furthermore, △XCO2 and NO2 are positively correlated with emission intensity and the proportion of emissions from the machinery industry, SO2 is negatively correlated with the proportion of chemical industry emissions, and SO2/NO2 is negatively correlated with emission efficiency and the proportion of light industry emissions. Results of the study show that the comprehensive satellite observation characteristics of atmospheric pollutants can be a reliable reference in evaluating industrial emission characteristics.

Patent Analysis of the Development of Technologies Applied to the Combustion Process

The use of combustion in industrial activity is of paramount importance for economic and social development. However, combustion reactions are the main sources of atmospheric pollutant emissions. Given this reality, it is necessary to study new combustion techniques, such as the application of oxygen in the process, in order to increase the efficiency and productivity of the burning process and energy production. In addition, studies have reported the use of acoustic excitation, a low-investment technique that can promote higher rates of heat and mass transfer. Thus, the goal of this study was to bring data on the current scenario related to the application of these two technologies to the combustion process where, through the reported results, they can be used as a guide for companies’ decisions about new technologies and global trends to be identified. For this, a technological prospection was carried out which focused on patents to investigate the use of oxygen-enhanced combustion and acoustic excitation coupled to the combustion process; a total of 88 documents were found. Few documents applied acoustic excitation for process improvement, indicating that its use is recent; however, according to the literature, it is a promising field to be explored. Siemens AG was the main depositor, and ten primary inventors were identified. Germany and the United States were the countries with the highest number of filings. In the prospected documents, it was possible to identify that there is a need for the further investigation of the joint use of both techniques. These investigations may lead to the development of processes and devices that can provide economic and environmental gains for the energy industry.

BONMIN solver-based coordination of distributed FACTS compensators and distributed generation units in modern distribution networks

The problems of increasing electricity consumption and atmospheric pollutants emissions are targeted as critical challenges for power transfer in modern distribution networks. In order to tackle this issue, many researchers have proposed the incorporation of Distributed Generator (DG) units, as well as different types of reactive power compensation devices, which will contribute to the increase of networks efficiency through loss minimization, voltage profile improvement, or even increasing transmission line’s capacity. This paper addresses the optimal allocation/coordination of DG, Distributed Static VAR Compensator (D-SVC), and Distributed Thyristor-Controlled Series Compensator (D-TCSC) to reduce total power loss in the distribution network. The allocation problem is formulated as a mixed-integer nonlinear programming (MINLP) and is solved using a basic open-source MINLP (BONMIN) solver embedded in GAMS. The proposed method was tested in IEEE 16-bus and 33-bus distribution test systems, where two cases were considered. Firstly, BONMIN solver is used for allocation of D-SVC, and D-TCSC, respectively, where the results showed that incorporation of these devices leads to reduction of the active power losses, while the minimal losses and highest efficiency increase for both test networks occurred in the case where 3 D-TCSCs allocated. Secondly, a coordinated allocation of DGs and D-SVCs, as well as DGs and D-TCSCs, is presented, where it was shown that coordination of these devices leads to even greater loss reduction, i.e. increased efficiency. Also, it was concluded that DG and D-TCSC coordination is better suited for loss reduction in the 16-bus system, while DG and D-SVC coordination leads to greater loss reduction for the 33-bus system. Furthermore, the comparison between BONMIN and metaheuristic methods was performed for DG allocation and DG and D-TCSC coordination in IEEE 33-bus system, where it was concluded that BONMIN performs better in terms of minimal power loss, compared to the results which were presented in the available literature. Finally, the BONMIN solver’s performance is evaluated using three parameters: number of nodes, number of iterations, and total execution time, where the numerical analysis showed that BONMIN is efficient in solving the addressed problems.

Sustainable Management of Salt Slag

The management of salt slag, a waste from the secondary aluminum industry, is associated with huge environmental concerns due to the risk of atmospheric pollution (emission of toxic gases), groundwater contamination (high salt content that can percolate and cause an increase in salinity) and soil unavailability (large extensions required for disposal). Therefore, the development of a sustainable process for its treatment and recovery is of the utmost importance. In this work, a two-step process for the valorization of salt slag was developed that rendered zeolite as the main added-value product and NaCl and NH3 as byproducts. First, salt slag was hydrolyzed at 90 °C and at a solid/water ratio of 1/3. More than 90% of salt and ~90% of ammonia were recovered. In a second step, the hydrolyzed slag was completely transformed into a NaP zeolite under mild hydrothermal conditions. The zeolite exhibited specific surface area (17 m2 g−1), cation exchange capacity (2.12 meq g−1) and zeta potential (−52 mV) values that represent good characteristics for use in the removal of metal ions from aqueous effluents. The transformation of salt slag into zeolite can be considered a sustainable process with a high contribution to the circular economy.

Cement industry – Associated emissions, environmental issues and measures for the control of the emissions

The cement industry though the backbone of modern construction and civilization is associated with the emission of diverse atmospheric pollutants with numerous attendant effects on the balance of ecosystem, human and environmental health and the global climate in general. Despite the huge advantages derivable from the industry, exploitation and processing of cement must be done in a sustainable manner to prevent irreversible damage to human, animal and vegetation health as well as the environment. Research papers were reviewed from different databases like ScienceDirect, ResearchGate, Google scholar, and Scopus the chief air pollutants are the inorganic gaseous emissions (carbon dioxide (CO2), carbon monoxide (CO), oxides of nitrogen (NOx), oxides of sulphur SO2), particulates of various size ranges and elemental emissions. The present study carries out holistic review of the cement production process with a view to identifying the principal air pollutants, sources and associated environmental issues. The study also reviews the pollution control measures currently in use and calls for a concerted effort from researchers, industry operators and regulators at working to reduce emissions with a view to upholding environmental sustainability.

Anatomy of the atmospheric emissions from the transport sector in Greece: trends and challenges.

Emissions of atmospheric pollutants are well-known for their adverse effects on air quality and public health. Additionally, GHG emissions are responsible for the so called “Radiating Forcing” leading to climate change and degradation of ecosystem services. In this work, we analyze the annual emission trends of various air pollutants, including GHGs, from all 4 sectors of transport (roads, aviation, navigation, and railway) in Greece during the 28-year period between 1990 and 2017, in order to examine the confounding dynamics among external forces, such as the major fiscal recession of 2008, and the GHG/pollutant emissions in the country. The analysis is performed with a suite of statistical tools consisting of bivariate correlation analysis, Mann–Kendall test, Sen’s slope estimation, and Joinpoint regression analysis, in order to thoroughly study the trends of emissions. It is found that all transport sectors (except for the railway) show a significant increase in their emissions, despite the fiscal recession of 2008 that temporarily decelerated all aspects of economic activity in the country. Given the major share of transport in GHG emissions (37%) and air pollution in urban centers, it is essential that the road sector adapts to the new challenges, by means of switching to low-emission technologies and electromobilization. The same applies for the navigation and aviation sectors, which are known pillars of the tourist industry in the country.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-021-18062-5.

Impact of lockdown and crop stubble burning on air quality of India: a case study from wheat-growing region.

The emergence of COVID-19 has brought the entire planet to a halt. Many countries, including India, were compelled to shut down most urban, industrial, social and other activities as a result of the pandemic. Due to a series of complete lockdowns imposed in India from March 24 to May 17, 2020, and state-wise local level restrictions afterward, have resulted in significant reduction of emissions of numerous atmospheric pollutants. The objective of this study is to analyse the change in concentration of various pollutants such as nitrogen oxide (NO2), carbon monoxide (CO) and aerosol optical depth (AOD) due to lockdown and also to quantify the contribution of crop stubble burning to air pollution. The Sentinel-5P based NO2 and CO observations for 2019 and 2020 and Moderate Resolution Imaging Spectroradiometer (MODIS)-based AOD observations for 2016–2020 were used for detecting the variations. The obtained results showed a significant decrease in NO2 levels during various stages of lockdown. Small decrease in CO levels was observed across most part of the India. With a few exceptions, such as coastal and desert regions, there was a moderate decrease in AOD levels. Furthermore, to study the contribution of NO2, CO and AOD from crop stubble burning, MODIS observations on active fire events were obtained from Visible Infrared Imaging Radiometer Suite (VIIRS). The burning of crop stubble increased NO2 emissions by 22 to 80%. CO levels, on the other hand, have risen by 7 to 25%. A considerable variation in AOD was reported, ranging from 1 to 426%.

Atmospheric Emission Sources in the Po-Basin from the LIFE-IP PREPAIR Project

This paper presents the focus on emission estimates in the Italian Regions of the Po-basin obtained by the development of a common air pollutant emission dataset on the Po-basin and Slovenia foreseen in the project LIFE PREPAIR (https://www.lifeprepair.eu/). The objective is to update emission inventories developed by the environmental protection agencies and regions of Lombardy, Emilia-Romagna, Piedmont, Veneto, Friuli Venezia Giulia, Valle d’Aosta, the province of Bolzano (participating as stakeholder) and the province of Trento. A data flux is defined considering the activities on emission estimates by the different administrations according to the current Italian legislation. This activity has allowed the completion of two different datasets on the area for 2013 and 2017. The estimates of primary emissions of the main atmospheric pollutants have a high spatial resolution defined at the municipal level. The non-industrial combustion of biomass in small domestic appliances is the main source of primary PM10 in the Po-basin. NOx primary emissions are determined for quite of a half by road transport. Manure management and fertilization in the agriculture sector are the sources of NH3. The ensemble of the collected data shows a very good comparability even if all local compilers perform independently the estimates, thanks to a good alignment in using reference methodologies and to projects of common methodological development, as reported by the INEMAR project (https://www.inemar.eu/). The estimates of PM10, NOx and NH3 are comparable with data reported by the European Environment Agency EEA for the European Member States EU-28 (until 1 February 2020) and for Italy, reported under the UNECE Convention on Long-range Transboundary Air Pollution and European Union National Emission Ceiling Directive.

Estimation of Atmospheric Pollutant Emissions from Vessels in Major Harbor Cities in Korea and related Social Cost

Estimation of Atmospheric Pollutant Emissions from Vessels in Major Harbor Cities in Korea and related Social Cost

Reducing emissions of atmospheric pollutants along major dry bulk and tanker routes through autonomous shipping

The present study investigates the environmental benefits of phasing-in autonomous ships in global maritime transportation along major dry bulk and tanker routes using Bayesian probabilistic forecasting algorithm. The focus is on the simulations and calibrations on the navigational behavior of autonomous ships at both port and high-sea, as well as the potential emission abatement of atmospheric pollutants compared to the conventional fleet along the sailing routes. We use historical data on major international tanker and dry bulk trade routes to characterize the ship movements and trends in ship emission. Different scenarios are evaluated with a combination of autonomous ship phase-in rates (25, 75, 100%) and cleaner fuel choices in Years 2030 and 2050 (from the baseline Year, 2020). The results show that the magnitude of the emission reduction generally increases with a higher level of autonomous ships in the fleet as expected, and the magnitude ranges from small increments to major reductions of 37–64% along the different routes. Overall, we hope that our findings can contribute towards the realization of environmental benefits with the adoption of autonomous shipping along the major shipping routes in the future.

The potential risks and exposure of Qinling giant pandas to polycyclic aromatic hydrocarbon (PAH) pollution

Rapid industrialization and urbanization have created a substantial urban-rural gradient for various pollutants. The Qinling Mountains are highly important in terms of biodiversity, providing habitat for giant pandas, which are endemic to China and are a widely recognized symbol for conservation. Whether polycyclic aromatic hydrocarbon (PAH) exposure risks regarding in situ animal conservation zones are affected by environmental pollution or even enhanced by the mountain-trapping effect requires further research. Our group carried out a large-scale investigation on the area ranging from Xi'an to Hanzhong across the giant panda habitat in the Qinling Mountains by collecting atmosphere, soil, bamboo, and fecal samples from different sites over a two-year period. The total toxicity of atmospheric PAHs and the frequencies of soil PAHs above effect range low (ERL) values showed a decreasing trend from urban areas to the central mountains, suggesting a distance effect from the city. The proportions of total 5- and 6-ring PAHs in the atmosphere were higher in the central mountainous areas than in the urban areas, while this difference was reversed in the soil. Health risk assessments showed that the incremental lifetime carcinogenic risks (ILCR) of PAH exposure by bamboo ingestion ranged from 2.16 × 10−4 to 3.11 × 10−4, above the critical level of 10−4. Bamboo ingestion was the main driver of the PAH exposure risks. The concentration difference between bamboo and fecal samples provided a reference for the level of PAHs absorbed by the panda digestive system. Since the Qinling Mountains possess the highest density of giant pandas and provide habitats to many other endangered animal and plant species, we should not ignore the probability of health risks posed by PAHs. Monitoring the pollution level and reducing the atmospheric emissions of toxic pollutants are recommended actions. Further detailed research should also be implemented on pandas' health effects of contaminant exposure.

Global research on the air quality status in response to the electrification of vehicles

Electric vehicles (EVs) can substantially decrease atmospheric pollutant emissions, thereby improving air quality, decreasing global warming, and improving human health. In this study, we performed a comprehensive bibliometric analysis using Web of Science to understand the research developments and future perspectives in EVs between 1974 and 2021. The analysis of indicators such as research trends, publication growth, and keywords revealed that most research in the selected timeframe was focused on applying and optimizing the existing technologies of different types of EVs to decrease air pollution and mortality. The changes in air quality owing to such electrification received special attention, with approximately 441 publications preferably in the English language. Among all the retrieved documents, research articles were most common (n = 295; 66.89% of the global output), dominated by the research domains of environmental sciences, followed by energy fuels and transportation science technology. Journal analysis revealed that Sustainability (n = 19, 4.30%) was the leading journal, followed by Journal of Cleaner Production and Science of the Total Environment. The most frequently used keywords were “electric vehicles,” “air quality,” and “air pollution.” The most highly impactful article was published by Jacobson et al. (2005) in Science, with 620 total citations and 38.82 average annual citations. Furthermore, the United States (n = 118; 26.75% of the global output) had the highest publication rate, followed by China and the United Kingdom. The leading institutions were Tsinghua University (n = 16; 3.62% of the global research output) in China, followed by the University of Michigan and Cornell University in the United States. The current analysis warrants more focus on comprehensive analysis employing transport and chemistry modeling and using the latest technology for long life and sustainable batteries. This study provides a basis for future studies on improving air quality through innovative work in the electrification of vehicles.

Abatement of atmospheric pollutant emissions with autonomous shipping in maritime transportation using Bayesian probabilistic forecasting

This study examines the potential abatement of environmental pollutant emissions with the adoption of autonomous vessels in future maritime transportation using Bayesian probabilistic forecasting algorithm. The emission reductions can be attributed to the related technological advancement, including particularly the improvements in navigational performance and berthing in port, which can achieve better efficiencies and lower fluctuations in sailing speeds. The scenario modeling approach is first established based on the foreseeable development of energy policies and usage as well as ship operations. Subsequently, assessment is performed in five major ports worldwide, namely Shanghai, Singapore, Long Beach, Hamburg, Tokyo from Year 2020 to 2050. The results are compared to the corresponding projections with manned shipping to determine the probabilistic emission abatements with the gradual adoption of autonomous ships into the fleet. Overall, the results provide a better understanding of the future environmental benefits with autonomous shipping to the policymakers, shipowners, and shipping industry.

Unsupervised PM2.5 anomalies in China induced by the COVID-19 epidemic

To stop the spread of COVID-19 (2019 novel coronavirus), China placed lockdown on social activities across China since mid-January 2020. The government actions significantly affected emissions of atmospheric pollutants and unintentionally created a nationwide emission reduction scenario. In order to assess the impacts of COVID-19 on fine particular matter (PM2.5) levels, we developed a “conditional variational autoencoder” (CVAE) algorithm based on the deep learning to discern unsupervised PM2.5 anomalies in Chines cities during the COVID-19 epidemic. We show that the timeline of changes in number of cities with unsupervised PM2.5 anomalies is consistent with the timeline of WHO's response to COVID-19. Using unsupervised PM2.5 anomaly as a time node, we examine changes in PM2.5 before and after the time node to assess the response of PM2.5 to the COVID-19 lockdown. The rate of decrease of PM2.5 around the time node in northern China is 3.5 times faster than southern China, and decreasing PM2.5 levels in southern China is 3.5 times of that in northern China. Results were also compared with anomalous PM2.5 occurring in Chinese's Spring Festival from 2017 to 2019, PM2.5 anomalies during around Chinese New Year in 2020 differ significantly from 2017 to 2019. We demonstrate that this method could be used to detect the response of air quality to sudden changes in social activities.

Government environmental control measures on CO2 emission during the 2014 Youth Olympic Games in Nanjing: Perspectives from a top-down approach

Strict air pollution control measures were conducted during the Youth Olympic Games (YOG) period at Nanjing city and surrounding areas in August 2014. This event provides a unique chance to evaluate the effect of government control measures on regional atmospheric pollution and greenhouse gas emissions. Many previous studies have observed significant reductions of atmospheric pollution species and improvement in air quality, while no study has quantified its synergism on anthropogenic CO2 emissions, which can be co-reduced with air pollutants. To better understand to what extent these pollution control measures have reduced anthropogenic CO2 emissions, we conducted atmospheric CO2 measurements at the suburban site in Nanjing city from 1st July to 30th September 2014 and 1st August to 31st August 2015, obvious decrease in atmospheric CO2 was observed between YOG and the rest period. By coupling the a priori emission inventory with atmospheric transport model, we applied the scale factor Bayesian inversion approach to derive the posteriori CO2 emissions in YOG period and regular period. Results indicate CO2 emissions from power industry decreased by 45%, and other categories also decreased by 16% for manufacturing combusting, and 37% for non-metallic mineral production. Monthly total anthropogenic CO2 emissions were 9.8 (±3.6) × 109 kg/month CO2 for regular period and decreased to 6.2 (±1.9) × 109 kg/month during the YOG period in Nanjing city, with a 36.7% reduction. When scaling up to whole Jiangsu Province, anthropogenic CO2 emissions were 7.1 (±2.4) × 1010 kg/month CO2 for regular period and decreased to 4.4 (±1.2) × 1010 kg/month CO2 during the YOG period, yielding a 38.0% reduction.

Impacts of the COVID-19 epidemic on merchant ship activity and pollution emissions in Shanghai port waters

This study aims to evaluate impacts of the COVID-19 epidemic on merchant ship activities and corresponding atmospheric pollutant emissions in Shanghai port waters. Comparing AIS data from February 2019 and from February 2020, it is found that the merchant ship count and utilization frequency are reduced during the epidemic period. The epidemic could result in longer ship turnaround times because of more operation time for berthing and anchoring activities. Ship emission comparison results reveal that the cargo ship emissions are significantly reduced while container ships and tankers produce a slightly decreased emissions resulting by strict COVID-19 quarantine measures. In addition, the unit ship emission intensity is greatly reduced for ships which are under the normal cruising status while berthing and anchoring operations are associated with increased ship emissions. This implies that it is urgent to promote the use of shore power equipment for merchant ships during the epidemic period.

Multi-objective programming for energy system based on the decomposition of carbon emission driving forces: A case study of Guangdong, China

Energy-related carbon emissions are increasing the rate of climate change, and controlling carbon emissions is a common challenge for the international public. Despite attempts to restrict the utilization of fossil energy and advancing technology for cleaner production, there has been little discussion on the determinants of change in carbon emissions for future scenarios and planning energy systems according to the analysis of low carbon development. In this study, a comprehensive energy optimization planning framework under a low-carbon mode is established. A framework based on the gray model (GM) and logarithmic mean Divisia index (LMDI) method are constructed to predict the emission mitigation potential and decompose the carbon emission driving factors. The decomposition results are key input prerequisites for the following energy optimization model: An interval parameter multiple-objective programming (IPMOP) optimization model, which is developed to support regional energy system administration by seeking the trade-offs among economic development, energy utilization, and environmental protection under multiple uncertainties. Furthermore, the proposed approach is applied to a case study in Guangdong, China. The results reveal that (a) the clean production effect (GDP per unit of atmospheric pollutants emission) would become the primary positive force for carbon emission increase, and the pollutant reduction effect (total atmospheric pollutants emission) would play the primary negative role; (b) the coal-dominated energy structure in Guangdong is expected to be transformed to a petroleum-dominated energy structure; (c) the GDP in Guangdong would steadily increase over time, but the pace of economic growth will decelerate, and the annual average growth rate of GDP for the coming fifteen years will be [3.67%, 4.26%]. This study provides a new pathway for policymakers to identify the determinants of carbon emission increase and to generate optimal solutions on a regional scale.

Study on Ship-based Atmospheric Pollutant Emission Forecasting for Environmental Impact Assessment in Port Planning

Vessels are major contributors to port-related atmospheric pollution. In recent years, as the environmental impact assessment s(hereinafter as EIA) in port planning become increasingly standardized, the lens on atmospheric pollution in EIA has gradually broadened from loading and unloading, piling and storage by cargo types to include the impact of ship emissions. However, the impact analysis ship-based atmospheric pollutants in port areas lack quantitative methodologies for accurate calculation, in particular where annual forecasting is commissioned in annual planning. By combining the characteristics of Chinese port planning and mainstream calculation methods of ship emissions in the world, the study arrives at several recommendations on selecting methodologies for the calculating of ship-based emissions in the EIA process that are tailored different planning scenarios and data availability, serving as reference for EIA practitioners in their endeavors to calculate the atmospheric pollutant emissions from ships in the EIA process mandated by port planning.

Transport decarbonization in big cities: An integrated environmental co-benefit analysis of vehicles purchases quota-limit and new energy vehicles promotion policy in Beijing

In the deep decarbonization era against climate change, big cities set ambitious targets for road transport. As China’s capital, Beijing has very strict vehicles quota-limit policies. This study contributes to the literature for its innovations on the evaluation of quota-limit executive policy for big cities which few studies have studied, and its improved method with integrated analysis model which distinguish itself for including future co-benefit estimation and enterprise-level data analysis. This study estimates the energy consumption and health environmental co-benefit up to 2030, results show that the ambitious policy will significantly reduce both CO2 and key atmospheric pollutants emissions. Besides, the health economic loss from different illnesses attributed to NOX, CO, PM2.5 and HC will be 65 %, 61 %, 19 % and 57 % lower than reference scenario in 2030. During the energy transition, gasoline will still occupy the biggest proportion of the passenger sector fuel use in Beijing. However, the quota-limit policy will have significant integrated impact on both emission mitigation and avoiding public health damage. This study provides a good reference for big cities in other countries for both its improved method and the effectiveness of administrative decree policy for urban transport planning.