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Receiving international industrial transfer (mainly foreign direct investment, FDI) is extremely important for economic development but also brings negative environmental impacts for Southeast Asian developing countries (SEADCs). Due to relatively low labor costs and large market potential, SEADCs have become an attractive destination for industrial transfer after China, while studies were far from sufficient on the associated air pollutant emissions that would worsen air quality and threaten human health. We develop an exploratory framework to estimate the long-term trends of relevant air pollutant emissions in eight major SEADCs, including Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. During 1990-2018, the emissions generally show a fluctuating upward trend and increased significantly in Cambodia, Laos, Philippines, and Vietnam. The total emissions of CO, NMVOC, SO 2 , NO X , PM 2.5 , and NH 3 from the eight SEADCs increased from 19.0, 4.3, 3.6, 1.5, 0.5, and 0.4 kilotons (kt) to 391.6, 260.9, 271.1, 182.4, 48.4, and 12.2 kt, respectively. The emission growth in almost all SEADCs accelerated after 2008 and faster than FDI growth. The disparities in emissions among SEADCs basically grew first and then declined to a level lower than that of 1990, but generally exceeded the disparities in FDI. Productivity gain and emission intensity decrease primarily caused the emission growth and reduction, respectively. Relatively small reductions in emission intensity are found for NO X and SO 2 . In general, most SEADCs have utilized FDI for economic development without sufficient efforts on air pollutant emission controls. Our outcomes can inform the formulation and optimization of relevant policies reconciling economic development and air quality improvement in SEADCs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Industrial enterprises are one of the largest sources of air pollution. However, the existing means of monitoring air pollutant emissions are narrow in coverage, high in cost, and low in accuracy. To bridge these gaps, this study explored a predicting model for air pollutant emissions from foundry industries based on high-accuracy electricity consumption data and continuous emission monitoring system (CEMS). The model has then been applied to the calculation of air pollutant emissions from foundries without CEMS and the optimization of air pollutant emission temporal allocation factors. The results reveal that electricity consumption and PM emissions during the 2022 Beijing Winter Olympics have the same ascending and descending relationship. Furthermore, a cubic polynomial model between electricity consumption and flue gas flow is established based on the whole year data of 2021 (R 2  = 0.85). The relative errors between the PM emissions calculated by the model and the emission factor method are small (-17.09-24.12 %), and the results from the two methods revealed a strong correlation (r = 0.93, p < 0.01). In addition, the monthly PM emissions from foundries are mainly concentrated in spring and winter, and the daily emissions on weekends are significantly lower than those on workdays. These results can be useful for environmental regulation and optimization of air pollutant emission inventories of foundry industry., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The emissions reduction of CO 2 and air pollutants are the main task in China. The two have the same roots and they interact with each other. However, CO 2 and air pollutants are quite different in space, so it is of great practical significance to explore the spatial differences of their synergy. As PM 2.5 and O 3 are more concerned at present, thus, this paper examined the decoupling of CO 2 , PM 2.5 and O 3 from GDP in China's 296 cities using the latest available data from 2015 to 2016. And the spatial differences of synergy among CO 2 , PM 2.5 and O 3 were quantitatively analyzed by using spatial autocorrelation analysis and geographically weighted regression model. The results showed that: (1) The cities achieving the three synergy emissions reduction were mainly in the southeast of China. (2) Only 26 cities had achieved the strong decoupling of CO 2 , PM 2.5 and O 3 from GDP. (3) The synergy characteristics between CO 2 and PM 2.5 , CO 2 and O 3 were different. This paper put forward the policies according to the conclusions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

China implemented the Promoting the Big and Quashing the Small Policy (PBQSP) in 2007 to alleviate air pollution due to coal-fired power plants (CFPPs). However, how the policy affected the air pollutant emissions remains poorly understood. We compared the air pollutant emissions between decommissioned and newly-built CFPPs under the PBQSP by developing a plant-level supply chain emission inventory model, taking Shandong, China's top provincial-level coal power producer, as the case area. The results indicated that compared to a 27.4% increase in electricity produced in Shandong from 2010 to 2014, the NOx, particulate matter (PM), Hg, and SO 2 emissions disproportionately increased by 10.3%, 11.7%, 11.8% and 0.5%, respectively. It was found that the PBQSP policy has made great contribution to air pollution mitigation, as the supply chain emission intensities (emissions per kilowatt-hour) of NO X , PM, Hg and SO 2 of the newly-built CFPPs are three-quarters, two-fifths, three-fifths, and four-fifths lower, respectively, than those of the decommissioned CFPPs. However, coal transport route changes caused an increase in NO X , PM, and SO 2 emissions by 44.0%, 45.5%, and 55.6%, respectively, during the transportation stage, which offset the PBQSP overall mitigation effect. By building a comprehensive assessment framework for air pollutant control policies, our study provides insights for formulating coordinated mitigation measures for the pollutant-intensive industries, such as promoting efficient air pollutant control technologies including the spray dust suppression devices., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This paper seeks to account for differences in productivity of the industrial and non-industrial activities in the productivity analysis framework. The Luenberger productivity indicator is widely applied to analyze the productivity change, and can be decomposed as it follows the additive structure. But there have been few studies on sector operation performance and industrial structure involving both the industrial and non-industrial inputs, output and air pollutant emissions. Resorting on the China's province-level data on energy, output and air pollutants from 2006 to 2019, we find that the industrial SO 2 emissions, energy consumption and NO X emissions are the major factors leading to sector operation inefficiency. By decomposing the operation performance indicator (OPI), we observe that contribution to productivity change by energy consumption, air pollutant emissions and output is higher than contribution by the non-industrial variables. Furthermore, technical progress offsets negative efficiency growth. In order to implement energy conservation, emissions reduction and industrial restructuring at the provincial level, China's government should take efforts to improve the efficiency of non-industrial energy consumption and support the development of cleaner industries., Competing Interests: Declaration of competing interest The authors declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier B.V.)

In 2018, the International Organization for Standardization (ISO) 19867-1 "Harmonized laboratory test protocols" were released for establishing improved quality and comparability for data on cookstove air pollutant emissions, efficiency, safety, and durability. This is the first study that compares emissions [carbon dioxide, carbon monoxide, total hydrocarbons, methane, nitrogen oxides, fine particulate matter (PM 2.5 ), organic carbon, elemental carbon, and ultrafine particles] and efficiency data between the ISO protocol and the Water Boiling Test (WBT). The study examines six stove/fuel combinations [liquefied petroleum gas (LPG), pellet, wood fan, wood rocket, three stone fire, and charcoal] tested in the same US EPA laboratory. Evaluation of the ISO protocol shows improvements over previous test protocols and that results are relatively consistent with former WBT data in terms of tier ratings for emissions and efficiency, as defined by the ISO 19867-3 "Voluntary Performance Targets." Most stove types remain similarly ranked using ISO and WBT protocols, except charcoal and LPG are in higher PM 2.5 tiers with the ISO protocol. Additionally, emissions data including polycyclic aromatic hydrocarbons are utilized to compare between the ISO and Firepower Sweep Test (FST) protocols. Compared to the FST, the ISO protocol results in generally higher PM 2.5 tier ratings.

Estimating accurately airborne pollutant emissions source information (source strength and location) is important for achieving effective air pollution management or adequate emergency responses to accidents. Inversion method is one of the useful tools to identify the source parameters. The atmospheric dispersion scheme has been proven to be the key to determining the source inversion performance by influencing the accuracy of the dispersion models. Modifying the atmospheric dispersion scheme is an important potential method to improve the inversion performance, but this has not been studied previously. To fill this gap, a novel approach for parameter sensitivity analysis combined with an optimization method was proposed to improve the source inversion performance by optimizing empirical scheme. The dispersion coefficients σ y and σ z of the typical BRIGGS scheme under different atmospheric dispersion conditions were optimized and used for air pollutant dispersion and source inversion. The results showed that the prediction performance of the air pollutant concentrations was greatly improved with statistical indices |FB| and NMSE decreased by 0.22 and 2.07, respectively; FAC2 and R increased by 0.10, and 0.08, respectively. For source inversion, the results of the significance analysis suggested that the accuracy in the source strength and location parameter (x0) were both significantly improved by ∼271% (relative deviation reduced from 60.0% to 16.2%) and ∼121% (absolute deviation reduced from 27.6 to 12.5 m). The improvement of source strength inversion accuracy was more significant under unstable atmospheric conditions (stability class A, B, and C); the mean absolute relative deviation was reduced by 97.5%. These results can help to obtain more accurate source information and to provide reliable reference for air pollution managements or emergency response to accidents. This study provides a novel and versatile approach to improve estimation performance of pollutant emission sources and enhances our understanding of source inversion., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Modeling the air pollution implications of long-term energy transitions requires a downscaling process as an intermediate step between national-scale energy models and fine-scaled air quality models. Traditional "Grow-in-Place" (GIP) downscaling methods assume that future patterns of generator siting and emissions will be similar to those in the past. However, rapid technological change and shifting policy might yield very different future spatial patterns of power emissions. Here, we propose a "Site-and-Grow" (SAG) downscaling framework to couple the Electricity Market Module (EMM) of the National Energy Modeling System (NEMS) with the Community Multi-scale Air Quality (CMAQ) model to simulate future changes in emissions from power sector. The SAG framework consists of two steps. First, we downscale regional energy information to subregions using a modified generation expansion model under the assumption that economic fundamentals drive decisions at that scale. Second, we use GIS-based screening to locate potential sites for new power plants, and specify the final county-level placement using a multicriteria value function, assuming that land use and environmental constraints are most influential. The method is implemented in one EMM region (Carolinas and Virginia) as a case study. We compare spatial and temporal variability of downscaled emissions using both GIP and SAG methods, as well as emissions differences among four NEMS scenarios (base case, high natural gas consumption, high penetration of electric vehicles, and marine vessel electrification in ports). The results indicate that coal power plant emissions such as SO 2 and NO x continue to dominate emissions from all other traditional power plants even in 2040, which suggests that emission changes will mainly be determined by where old coal plants are retired. An ANOVA (analysis of variance) comparison of four energy scenarios with two downscaling methods shows that the choice of downscaling method can contribute as much to emissions patterns as much as the choice of scenario., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

This study implemented real-world tests in Nanjing, China for measuring emission factors (EFs) of air pollutants, including Carbon Monoxide (CO), Hydrocarbon (HC), Nitrogen Oxides (NO x ), and Particulate Matter (PM) from ten construction machines in three operational modes (idling, moving, and working) with a Portable Emission Measurement System. The idling mode shows the least variation of EFs, and its average CO EFs can be higher than the moving and working modes by 43% and 34%, respectively. The working mode generates the highest emission for all other pollutants with the highest variation. The EFs suggested by the Guide (an official guidebook for developing emission inventory in China) are in general lower than the measured EFs, and the gap becomes larger for older machines. The EFs of CO, NO x , and PM of China Stage II machines are 24%, 120%, and 66% higher than those of the Guide, respectively. The differences go up as high as 126%, 1066%, and 559% for China Stage I machines, indicating the upgrade of engine technology from Stage I to Stage II, as well as the effect of machine deterioration. The result of this study reveals the effectiveness of stringent emission standards in controlling emissions from construction machines. High emissions from older machines emphasize the importance of a more rigorous machine replacement policy and a regulated maintenance strategy. The result also stresses the need to update the Guide with differentiated activity modes, region variations, and machine deterioration effects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Since the most stringent-ever clean air policy was implemented in 2013 in China, main industrial air pollutant emissions have notably decreased. However, there are few studies on air pollutant emissions of industrial sectors driven by supply chain before and after implementing this policy. This paper attempts to provide a new perspective from industrial linkage to understand the emission of air pollutants. Based on Input-Output model framework, we revealed the linkages of SO 2 and NO x emissions between sectors from 2012 to 2017 and the driving forces behind emission changes. Moreover, we simulated the possible impact of the key sector linkages on air pollutant emissions. Results show that the most noteworthy change during this period is that the metal melting sector has replaced the power sector, as the largest pollutant output emission sector associated with other sectors, especially the transport equipment sector. The main reason of this phenomena is that the emission intensity reduction rate of metal smelting sector (e.g., only 17% for NO x ) is far less than other sectors. In the future, the development of the equipment manufacturing may put pressure on the metal smelting sector to reduce emissions. For example, when the transport equipment sector increases total output by 20% ~ 40%, the metal smelting sector will be driven to emit 0.04Mt ~0.08Mt of NO x . This paper provides a basis to quantitatively analyze the industrial sector linkages and identify the key sectors from 2012-2017, and helps decision makers better understand the impact of sector linkage on pollutant emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Meteorology and long-term trends in air pollutant concentrations may obscure the results from short-term policies implemented to improve air quality. This study presents changes in CO, NO 2 , O 3 , SO 2 , PM 10 , and PM 2.5 based on their anomalies during the COVID-19 partial (Phase 2) and total (Phase 3) lockdowns in Mexico City (MCMA). To minimise the impact of the air pollutant long-term trends, pollutant anomalies were calculated using as baseline truncated Fourier series, fitted with data from 2016 to 2019, and then compared with those from the lockdown. Additionally, days with stagnant conditions and heavy rain were excluded to reduce the impact of extreme weather changes. Satellite observations for NO 2 and CO were used to contrast the ground-based derived results. During the lockdown Phase 2, only NO 2 exhibited significant decreases ( p < 0.05) of between 10 and 23% due to reductions in motor vehicle emissions. By contrast, O 3 increased ( p < 0.05) between 16 and 40% at the same sites where NO 2 decreased. During Phase 3, significant decreases ( p < 0.05) were observed for NO 2 (43%), PM 10 (20%), and PM 2.5 (32%) in response to the total lockdown. Although O 3 concentrations were lower in Phase 3 than during Phase 2, those did not decrease ( p < 0.05) from the baseline at any site despite the total lockdown. SO 2 decreased only during Phase 3 in a near-road environment. Satellite observations confirmed that NO 2 decreased and CO stabilised during the total lockdown. Air pollutant changes during the lockdown could be overestimated between 2 and 10-fold without accounting for the influences of meteorology and long-term trends in pollutant concentrations. Air quality improved significantly during the lockdown driven by reduced NO 2 and PM 2.5 emissions despite increases in O 3 , resulting in health benefits for the MCMA population. A health assessment conducted suggested that around 588 deaths related to air pollution exposure were averted during the lockdown. Our results show that to reduce O 3 within the MCMA, policies must focus on reducing VOCs emissions from non-mobile sources. The measures implemented during the COVID-19 lockdowns provide valuable information to reduce air pollution through a range of abatement strategies for emissions other than from motor vehicles., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Hernández-Paniagua, Valdez, Almanza, Rivera-Cárdenas, Grutter, Stremme, García-Reynoso and Ruiz-Suárez.)

On December 31, 2019, the Chinese authorities reported to the World Health Organization (WHO) the outbreak of a new strain of coronavirus that causes a serious disease in the city of Wuhan, China. This outbreak was classified as SARS-CoV2 and is the cause of the COVID-19 disease. On March 11, 2020, the WHO declares it a Pandemic and today it is considered the greatest challenge in global health that humanity has faced since World War II and it is estimated that between 40 and 60% of the population worldwide will catch the virus. This has caused enormous challenges in countries around the world in social, economic, environmental and obviously health issues. These challenges are mainly due to the effects of the established quarantines in almost all capitals and major cities around the world, from Asia, Europe to America. However, these lockdown which began worldwide from January 23, have had a significant impact on the environment and on the air quality of cities as recently reported by NASA (National Aeronautics and Space Administration) and ESA (European Space Agency), with reductions according to them of up to 30% in some of the epicenters such as the case of Wuhan. Knowing that air pollution causes approximately 29% of lung cancer deaths, 43% of COPD deaths, and 25% of ischemic heart disease deaths, it is important to know the effects of quarantines in cities regarding air quality to take measures that favor populations and urban ecosystems when the emergency ends. Therefore, this paper describes the behavior of PM 2.5 emissions particulate matter from the 50 most polluted capital cities in the world according to the WHO, measured before-after the start of the quarantine. Likewise, the impact at the local and global level of this emissions behavior, which averaged 12% of PM 2.5 decrease in these cities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The active use of solid fossil fuels (coal) in the production of heat and electricity has led to significant pollution, climate change, environmental degradation, and an increase in morbidity and mortality. Many countries (in particular, European ones, China, Japan, the USA, Canada, etc.) have launched programs for using plant and agricultural raw materials to produce heat and electricity by burning them instead of or together with traditional fuels. It is a promising solution to produce slurry fuels, based on a mixture of coal processing, oil refining and agricultural waste. This paper presents the results of experimental research into the formation and assessment of the most hazardous emissions (sulfur and nitrogen oxides) from the combustion of promising coal slurry fuels with straw, sunflower and algae additives, i.e. the most common agricultural waste. A comparative analysis has been carried out to identify the differences in the concentrations of sulfur and nitrogen oxides from the combustion of typical coal, coal processing waste, as well as fuel slurries with and without plant additives. It has been shown that the concentration of sulfur and nitrogen oxides can be reduced by 62-87% and 12-57%, respectively, when using small masses of plant additives (no more than 10 wt%) and maintaining high combustion heat of the slurry fuel. However, the use of algae and straw in the slurry composition can increase the HCl emissions, which requires extra measures to fight corrosion. A generalizing criterion of slurry fuel vs. coal efficiency has been formulated to illustrate significant benefits of adding plant solid waste to coal-water slurries containing petrochemicals. Straw and sunflower waste (10 wt%) were found to be the best additives to reduce the air pollutant emissions., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Environmental pollution and the associated societal health issues have attracted recent research attention. While most research has focused on the effect of air pollution on human health and local economies, few articles have discussed the environment, health, and economic development in in an integrated analysis. This paper used a Dynamic Network SBM Model to evaluate production and health efficiencies in Chinese cities and found that the production efficiency scores were slightly higher than the health efficiency scores, with the two-stage efficiency scores in most cities having significant fluctuations. Labor, fixed assets, energy, GDP, and lung disease and mortality reduction efficiencies in the first stage were generally high; however, the medical input efficiencies in the second stage were low, indicating that there was there significant room for improvement in many cities.

Pollutant emissions from incomplete combustion of raw coal in low-efficiency residential heating stoves greatly contribute to winter haze in China. Semi-coke coals and improved heating stoves are expected to lower air pollutant emissions and are vigorously promoted by the Chinese government in many national and local plans. In this study, the thermal performance and air pollutant emissions from semi-coke combustion in improved heating stoves were measured in a pilot rural county and compared to the baseline of burning raw coal to quantify the mitigation potential of air pollutant emissions. A total of five stove-fuel combinations were tested, and 27 samples from 27 different volunteered households were obtained. The heating efficiency of improved stoves increased, but fuel consumption appeared higher with more useful energy output compared to traditional stoves. The emission factors of PM 2.5 , SO 2 , and CO 2 of semi-coke burning in specified improved stoves were lower than the baseline of burning raw coal chunk, but no significant NOx and CO decreases were observed. The total amount of PM 2.5 and SO 2 emissions per household in one heating season was lower, but CO, CO 2 , and NOx increased when semi-coke coal and specified improved stoves were deployed. Most differences were not statistically significant due to the limited samples and large variation, indicating that further evaluation would be needed to make conclusions that could be considered for policy., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

This article describes a pilot test at a sewage sludge incineration plant and shows its results considering the impacts of reducing the minimum combustion temperature from 850°C to 800°C. The lowering leads to an actual reduction of the average combustion temperature by 25 K and a significant reduction in the fuel oil consumption for support firing. The test shall be used for providing evidence that the changed combustion conditions do not result in higher air pollutant emissions. The analysis focusses on the effects of the combustion temperature on nitrogen oxides (NO x ) and total organic carbon emissions. The evaluation of all continuously monitored emissions shows reduced emission levels compared to the previous years, especially for NO x .