Reduce Air Pollution Research Articles

China's progress in synergetic governance of climate change and multiple environmental issues.

Advancing the synergetic control of climate change and environmental crisis is crucial for achieving global sustainable development goals. This study evaluates synergetic governance levels over climate change and four environmental issues at the provincial level in China from 2009 to 2020. Our findings reveal significant progress in China's coordinated efforts to mitigate carbon emissions, reduce air pollutants, and conserve water resources. However, there remains room for improvement in managing solid waste and protecting ecological systems and overall progress in synergetic governance has slowed since 2015. Employing a random forest model, we identify socio-economic factors with great influence on synergetic climate change and environmental governance, such as energy intensity, service sector development, electronic equipment manufacturing, and transportation. Additionally, we reveal nonlinear relationships between some factors and performance of environmental subsystems, including both plateau effects (e.g. output in the smelting of ferrous metals) and U-shaped patterns (e.g. output in the manufacturing of metal products), possibly attributed to constraints in end-of-pipe treatment capacities and complexities in supply chain networks. Furthermore, through hierarchical clustering analysis, we classify provinces into four groups and provide tailored recommendations for policymakers to enhance synergetic governance levels in their respective regions. The framework established in this study also serves as a valuable reference for countries seeking to develop practical and context-specific solutions to mitigate climate and environmental risks.

The effect of different climate and air quality policies in China on in situ ozone production in Beijing

Abstract. In recent years, clean air policies have led to reductions in air pollution across China. Alongside this, emerging carbon neutrality (CN) policies that aim to address the impacts of climate change may also deliver air quality (AQ) co-benefits or climate penalties. Different CN policies will lead to different changes in volatile organic compound (VOC), NOx and particulate matter (PM) emissions, which will in turn impact the photochemical production of secondary pollutants such as ozone (O3). It is currently unclear how different combinations of AQ and CN policies may impact in situ O3 production across China in the future. A detailed chemical box model incorporating the Master Chemical Mechanism was developed to investigate the impact of combined AQ and CN policies on O3 formation in Beijing. The Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) and the Dynamic Projection model for Emissions in China (DPEC) were used to estimate future pollutant mixing ratios, relative to ambient observations of 35 VOCs, NOx, CO and aerosol surface area (ASA) during the APHH-Beijing 2017 summer campaign. The most ambitious policy scenario, “Ambitious Pollution 1.5D Goals”, led to the largest reduction in O3 production by 2060 but was not the most impactful scenario for reducing O3 production between 2030–2045. Larger reductions were observed under the “Ambitious Pollution Neutral Goals” policy, which focuses on achieving net zero by 2060. O3 production was found to be most sensitive to changes in the OLE2 group of VOCs (alkenes where kOH>7×104 ppm−1 min−1; a 5 % increase in OLE2 increased simulated O3 production by 1.12 %). However, reducing less reactive but higher concentration species in Beijing (such as short-chain alkanes) led to larger reductions in O3 production under all scenarios. O3 production was not sensitive to changes in ASA, with a 69 % decrease in ASA leading to a change of <1 % in O3. However, doubling biogenic VOCs in the model further increased O3 production in 2060 under all future scenarios by up to 18 %, indicating that the influence of future climate-induced changes in biogenic emissions may have a significant impact on in situ O3 formation in Beijing. This study highlights that the emission trajectories of certain specific VOCs are highly influential in determining possible future O3 air quality effects that may arise from increasing ambient temperatures and decarbonisation in Beijing.

The effect of the end-number license plate driving restriction on reducing air pollution in China

This study investigates the long-term efficiency of the long-run end-number license plate driving restriction in China, a traffic control policy that is partially aimed at reducing urban air pollution. A difference-in-differences regression is performed on a panel including nine cities that implemented this policy in staggered manner between 2008 and 2013. The results show that overall, this driving restriction does not improve air pollution in policy cities over the long-term. Quantitatively, the city-level air quality index has close-zero statistically insignificant changes by the policy, reaching only 3.9% reduction by 95% confidence interval lower bound of the estimate, translating to welfare gains of only 11.24 USD (70.62 CNY) per person per year, or 0.447 life years per capita. Further analysis with regression discontinuity in time and heterogeneity subgroup analysis illustrates that air pollution may first decrease due to the policy but then bounce back because of the behavioral adaptations of drivers purchasing a second car in cities without simultaneous car purchase restrictions. This shows that need to combine the end-number license plate policy with car purchase restrictions or electric vehicle promotions to achieve effective air pollution reductions over the long-term.

Identification and genomic analysis of a thermophilic bacterial strain that reduces ammonia loss from composting.

Ammonia loss is the most severe during the high-temperature stage (>50°C) of aerobic composting. Regulating ammonia volatilization during this period via thermophilic microbes can significantly improve the nitrogen content of compost and reduce air pollution due to ammonia loss. In this study, an ammonia-assimilating bacterial strain named LL-8 was screened out as having the strongest ammonia nitrogen conversion rate (32.7%) at high temperatures (50°C); it is able to significantly reduce 42.9% ammonia volatile loss in chicken manure composting when applied at a high-temperature stage. Phylogenetic analysis revealed that LL-8 was highly similar (>98%) with Priestia aryabhattai B8W22T and identified as Priestia aryabhatta. Genomic analyses indicated that the complete genome of LL-8 comprised 5,060,316 base pairs with a GC content of 32.7% and encoded 5,346 genes. Genes, such as gudB, rocG, glnA, gltA, and gltB, that enable bacteria to assimilate ammonium nitrogen were annotated in the LL-8 genome based on the comparison to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The results implied that the application of thermophilic ammonia-assimilating strain P. aryabhatta LL-8 would be a promising solution to reduce ammonia loss and mitigate air pollution of aerobic composting.IMPORTANCEAerobic composting is one of the essential ways to recycle organic waste, but its ammonia volatilization is severe and results in significant nitrogen loss, especially during the high-temperature period, which is also harmful to the environment. The application of thermophilic bacteria that can use ammonia as a nitrogen source at high temperatures is helpful to reduce the ammonia volatilization loss of composting. In this study, we screened and identified a bacteria strain called LL-8 with high temperature (50°C) resistance and strong ammonia-assimilating ability. It also revealed significant effects on decreasing ammonia volatile loss in composting. The whole-genome analysis revealed that LL-8 could utilize ammonium nitrogen by assimilation to decrease ammonia volatilization. Our work provides a theoretical basis for the application of this functional bacteria in aerobic composting to control nitrogen loss from ammonia volatilization.

The Urban Factor: Meta-analysis of Air Pollution and Cancer Incidence

Background: Urban air pollution is a significant environmental health concern associated with various adverse health outcomes, including cancer. Understanding the relationship between urban air pollution exposure and cancer incidence is crucial for informing public health interventions and policy decisions. Methods: A systematic review and meta-analysis will be conducted to investigate the association between urban air pollution exposure and cancer incidence. Eligible studies will be identified through comprehensive searches of electronic databases. Inclusion criteria encompassed studies reporting quantitative data on air pollution exposure and cancer outcomes. Data extraction and quality assessment will be performed according to predefined criteria. Results: The systematic search will be yielded X studies meeting the inclusion criteria for the meta-analysis. These studies, representing diverse geographic regions, employed various exposure assessment methods and included cohort, case-control, and cross-sectional designs. The meta-analysis will reveal a statistically significant association between urban air pollution exposure and overall cancer incidence (p < 0.05). The pooled effect will estimate indicated a X% increased risk of cancer per unit increase in air pollution exposure. Conclusion: Our meta-analysis provides robust evidence of a significant association between urban air pollution exposure and cancer incidence. These findings underscore the urgent need for targeted interventions to reduce air pollution levels in urban areas and mitigate cancer risks. Public health policies focusing on environmental quality improvements are crucial for promoting population health and well-being.

Designing Retirement Strategies for Coal-Fired Power Plants To Mitigate Air Pollution and Health Impacts.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system operations and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO2 emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and Rest of PJM, leading to scenario-varying changes in the plant-level release of air pollutants. Considering pollution transport and the size of the exposed population, these emissions changes, in turn, give rise to a reduction of 6-136 PM2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Among our designed scenarios, those that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, comparing across the six scenarios evaluated in this study, vulnerable populations─in both PA and Rest of PJM─benefit most in scenarios that prioritize plant closures near Environmental Justice Areas in PA. These results demonstrate the importance of considering cross-regional linkages and sociodemographics in designing equitable retirement strategies.

Recent advances in sustainable nanomaterials for energy conversion and environmental remediation via photocatalysis

Photocatalysis is of particular interest because it can be utilized for reducing air pollution and decreasing greenhouse gas emissions. This review examined the latest advances in layered photocatalytic nanomaterials and single-atom catalysts and discloses the synthesis, structural features, and ways to enhance their catalytic ability. In particular, we describe the peculiarities of catalysis mechanisms in CO2 conversion, pollutant and NOx removal, and nitrogen reduction. The current trends in this field and the potential areas for further research are also discussed in this review. It is important to emphasize that single-atom catalysts possess distinct advantages to substantially improve the efficiency of energy conversion processes. The materials related to the synthesizing and post-processing of layered semiconductor catalysts and single-atom catalysts can be useful for other researchers and stakeholders.

Economic Case for Replacing High-Emitting Peaker Plants with Fuel Cells for Automotive Applications.

The identification of clean and cost-effective solutions to replace high-emitting peaker plants and support a just transition is a challenge faced by utilities across the US today. However, falling costs of hydrogen production as well as the widespread availability of fuel cells for automotive applications have made them an attractive option for a zero-emission peak power supply. This study evaluates the techno-economics, operation, and environmental justice impacts of siting a peaker plant based on fuel cells for automotive applications through the lens of the existing Intermountain Power Plant, in order to supply peak power to the Los Angeles basin. Compared to the fossil fuel-fired peakers in operation today, the fuel cell peaker would be lower-cost up to a 17% capacity factor with Inflation Reduction Act incentives while also reducing air pollution in environmental justice communities. With corresponding transmission upgrades, the Intermountain site could host up to a 5 GW fuel cell peaker in the future.

Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression

ABSTRACT The study examines the relationship between air quality, meteorological factors, and COVID-19 cases in Cheras, Kuala Lumpur, and Kelapa Gading, North Jakarta. Analyzing data from 2020 and 2021, the research found notable correlations: COVID-19 cases in Cheras were positively associated with relative humidity (RH) and carbon monoxide (CO) but negatively with ozone (O₃) and RH in different years. In Kelapa Gading, COVID-19 cases were positively correlated with pollutants like sulfur dioxide (SO₂) and CO, while ambient temperature (AT) showed a negative correlation. The enforcement of social restrictions notably reduced air pollution, affecting COVID-19 spread. Predictive models for PM2.5 levels using robust regression techniques showed strong performance in Kuala Lumpur (R² > 0.9) but exhibited overfitting tendencies in Jakarta, suggesting the need for a longer study period for more accurate results.

MACHINE LEARNING METHODS APPLIED IN AIR QUALITY PREDICTION

Air quality is an important environmental component that has a significant influence on public health and well-being. Poor air quality can cause a variety of health problems, including respiratory and cardiovascular disorders. Therefore, there is a growing demand for air quality prediction tools to enable consumers and authorities to take the best decisions and to implement the necessary actions to reduce air pollution. The present paper describes an innovative application that uses machine learning techniques to supply to the users real-time air quality predictions made on past data from their unique location. The Scikit-learn Python package was used to implement five machine learning algorithms, including K-Nearest Neighbors, Random Forest, Gradient Boosting, Support Vector Regression (SVR) and AdaBoost. To achieve robust model performance, compatibility with cross-validation approaches was evaluated. The obtained results indicate that these machine learning techniques are successful at forecasting air quality. The AdaBoost method emerged as the best accurate predictor after extensive investigation, closely followed by Gradient Boosting, SVR, Random Forest, and K-Nearest Neighbors. Furthermore, the investigation also focused on the adapted handling of inaccurate data and providing graphical visualizations to highlight the algorithm's efficacy.

The effects of green finance on pollution and carbon reduction: Evidence from China’s industrial firms

Reducing pollution and carbon emissions is important but requires a large amount of capital. Green finance is becoming an important market-based instrument. Few literatures have focused on the direct impact of green finance on corporate environmental performance. This study investigates the effects of green finance on air pollution and carbon reduction in China’s industrial firms from 2008 to 2015. Results show that green finance promotes CO2 and air pollution reduction. Moreover, green finance has a synergistic effect on SO2 and carbon reduction, but not on reduction of dust and carbon emissions. Our findings suggest that green finance reduces emissions by improving corporate energy utilization efficiency. Furthermore, we find that the effects of green finance on emission reduction are more significant among non-state and non-listed firms. These findings have important implications for the development of green finance and synergistic reduction of air pollutants and carbon.

Integrated Benefits of Synergistically Reducing Air Pollutants and Carbon Dioxide in China.

China's advancements in addressing air pollution and reducing CO2 emissions offer valuable lessons for collaborative strategies to achieve diverse environmental objectives. Previous studies have assessed the mutual benefits of climate policies and air pollution control measures on one another, lacking an integrated assessment of the benefits of synergistic control attributed to refined measures. Here, we comprehensively used coupled emission inventory and response models to evaluate the integrated benefits and synergy degrees of various measures in reducing air pollutants and CO2 in China during 2013-2021. Results indicated that the implemented measures yielded integrated benefits value at 6.7 (2.4-12.6) trillion Chinese Yuan. The top five contributors, accounting for 55%, included promoting non-thermal power, implementing end-of-pipe control technologies in power plants and iron and steel industry, replacing residential scattered coal, and saving building energy. Measures demonstrating high synergies and integrated benefits per unit of reduction (e.g., green traffic promotion) yielded low benefits mainly due to their low application, which are expected to gain greater implementation and prioritization in the future. Our findings provide insights into the effectiveness and limitations of strategies aimed at joint control. By ranking these measures based on their benefits and synergy, we offer valuable guidance for policy development in China and other nations with similar needs.

Clearing the air: A systematic review of studies on air pollution and childhood brain outcomes to mobilize policy change

Climate change, wildfires, and environmental justice concerns have drawn increased attention to the impact of air pollution on children’s health and development. Children are especially vulnerable to air pollution exposure, as their brains and bodies are still developing. The objective of this systematic review was to synthesize available empirical evidence on the associations between air pollution exposure and brain outcomes in developmental samples (ages 0–18 years old). Studies were identified by searching the PubMed and Web of Science Core Collection databases and underwent a two-phase screening process before inclusion. 40 studies were included in the review, which included measures of air pollution and brain outcomes at various points in development. Results linked air pollution to varied brain outcomes, including structural volumetric and cortical thickness differences, alterations in white matter microstructure, functional network changes, metabolic and molecular effects, as well as tumor incidence. Few studies included longitudinal changes in brain outcomes. This review also suggests methodologies for incorporating air pollution measures in developmental cognitive neuroscience studies and provides specific policy recommendations to reduce air pollution exposure and promote healthy brain development by improving access to clean air.

Dietary Flavonoids: Mitigating Air Pollution's Cardiovascular Risks.

Air pollution significantly impacts cardiovascular health, yet pollution reduction strategies in cardiovascular disease prevention remain limited. Dietary flavonoids show promise in protecting cardiovascular health, but their potential to mitigate air-pollution-induced risks is unexplored. This study investigates this research gap. Following PRISMA-ScR guidelines, literature from 2014-2024 was searched across MedLine/PubMed, ScienceDirect, and MDPI databases. Of 463 identified studies, 53 were eligible for analysis based on PICO criteria. Findings revealed significant impacts of air pollution on cardiovascular health, including increased disease risks and mortality. Flavonoid intake demonstrated protective effects against these risks. Flavonoid mechanisms include improved endothelial function, antioxidant and anti-inflammatory effects, blood pressure regulation, antiplatelet effects, cardioprotection, and enhanced lipid and glucose metabolism. Higher flavonoid intake was consistently associated with reduced cardiovascular risks. While reducing pollution remains crucial, promoting flavonoid-rich diets is a promising complementary strategy. Public health initiatives should raise awareness about these benefits. Further research on direct interactions between flavonoid intake and air pollution exposure is needed. Current evidence supports integrating dietary interventions into broader strategies to reduce air pollution's cardiovascular impacts.

Implication of the EU Countries’ Energy Policy Concerning Scenarios Affecting the Air Quality Improvement

Energy policy has a significant impact on the state of the environment and, therefore, on residents’ health and life expectancy, especially in highly urbanized areas. Reducing emissions is currently one of the necessary actions that must be taken at the scale of individual countries to ensure sustainable development. The article aims to identify the best ways to shape energy policy by evaluating development scenarios for air protection and their environmental impact. The realization of the goal is based on the data included in three groups: (1) Economic factors, Health factors, and Demographic factors; (2) Clima-e related economic losses, Renewable Energy sources in electricity, heating, and cooling, Premature deaths due to exposure to fine particulate matter (PM2.5), Health impacts of air pollution, Population change; (3) Demographic balance and crude rates at the national level, GDP per capita in purchasing power PPS, GDP, and principal components; covering 36 EU countries in 2019 and 2021. The study proposes an advanced methodology for assessing development strategies by integrating the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Bayesian networks (BN) and incorporating them into a multicriteria decision-making (MCDM) support system. The TOPSIS model based on BN allowed for the illustration of the features of many criteria and the identification of relationships between scenarios, allowing for selecting the best way to develop energy policy. The results showed a 60.39% chance of achieving success in extending the life of residents by five years. At the same time, the most favorable development path was the scenario promoting activities aimed at reducing air pollution by introducing renewable energy sources to produce energy used for lighting and preparing domestic hot water urban areas. By presenting possible scenarios and the probability of success, it is possible to achieve the goal of practical energy policy at the level of the country and individual European cities and also by extending the life of city inhabitants, as presented by the authors in this study.

The Relationship between Green Infrastructure and Air Pollution, History, Development, and Evolution: A Bibliometric Review

In response to the challenge of atmospheric pollution posed by growing environmental problems, this study reviews and analyzes the research status and development trends of green infrastructure (GI) in improving air pollution from 2014 to 2024. Using the CiteSpace tool, we explore research hotspots, disciplinary developments, significant contributors, and influential literature in this field, identifying current research gaps and predicting future trends. The findings indicate that GI significantly impacts the reduction of air pollution, the regulation of urban microclimates, and the enhancement of ecosystem services. However, existing studies often focus on isolated aspects and lack comprehensive assessments. Moreover, the research trajectory in this field shows a declining trend. Future research should emphasize interdisciplinary integration, combining ecology, urban planning, meteorology, and public health. By utilizing advanced technologies, such as drones, remote sensing, AI, and big data analysis, we can improve data accuracy and the generalizability of research findings. Additionally, it is crucial to consider the performance of GI under different climatic conditions and socio-economic contexts to comprehensively quantify its overall benefits in terms of air quality, urban thermal comfort, public health, and economic impact. This comprehensive approach will provide a scientific basis for policy-making and urban planning.

Reduction of Air Pollution from IC Engine Exhausts Through Condensation with Novel Porous Copper Metal Foams

Reduction of Air Pollution from IC Engine Exhausts Through Condensation with Novel Porous Copper Metal Foams

Association between exposure to air pollution and arterial stiffness in participants with and without atherosclerotic cardiovascular disease.

To assess the association of air pollution exposure at different time scales with arterial stiffness in participants with and without atherosclerotic cardiovascular disease (ASCVD). We measured participants' arterial stiffness with brachial-ankle pulse wave velocity (baPWV) from October 2016 to January 2020. Concentrations of air pollutants including fine particles < 2.5μm aerodynamic diameter (PM2.5), inhalable particles < 10μm aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) measured by fixed ambient air monitoring stations were collected for short- (7-day) and long-term (365-day) exposure assessment. We used generalized estimating equations (GEEs) to analyze and further explored the modification effects between ASCVD and air pollutants. Seven hundred sixty-five participants were finally included and four hunderd sixty (60.1%) participants had a history of ASCVD. Based on the partial regression coefficients (β) and 95% confidence intervals (95% CI) calculated from GEEs using linear regression, each 10μg/m3 increase in long-term exposure to PM2.5 and PM10 was associated with 31.85cm/s (95% CI, 17.97 to 45.73) and 35.93cm/s (95% CI, 21.01to50.84) increase in baPWV. There was no association between short-term exposure to air pollution and arterial stiffness. Although no significant interaction effect was observed between air pollution and ASCVD, baPWV showed a greater increment in the subgroup without ASCVD. Long-term exposure to air pollution is closely associated with higher arterial stiffness in participants with and without ASCVD. Reducing air pollution exposure is essential in the primary and secondary prevention of ASCVD.

Digital transformation and synergistic reduction in pollution and carbon Emissions——An analysis from a dynamic capability perspective

Pollution control and carbon emission reduction pose significant challenges for developing countries, and achieving synergistic reductions in pollution and carbon emissions (SRPCs) has emerged as the optimal choice. Digitization, a prevailing trend in the current era, presents new opportunities for realizing the SRPC. We utilize data from Chinese A-share listed companies from 2007 to 2022 to investigate the impact of corporate digital transformation on the SRPC. The research reveals the following. (1) Enterprise digital transformation significantly promotes the SRPC, a conclusion validated through a series of robustness tests. However, the SRPC resulting from digital transformation is characterized by weak synergy, which is primarily observed in the coordinated reduction in air pollution and carbon emissions. (2) This effect is notably stronger for companies near environmental regulatory authorities, those receiving government environmental subsidies, and state-owned enterprises (SOEs). (3) Enhancing managerial collaborative management capabilities, promoting corporate technological innovation capabilities, and alleviating financing pressure are the primary mechanisms at play. This research provides important policy and practical insights for promoting the SRPC in the context of digitization, fostering sustainable development.

Quantifying the Co-benefits of Air Pollution and Greenhouse Gas emission mitigation by operating Metro Line 1 in Ho Chi Minh City, Vietnam

Abstract Motorcycles, cars, and buses in urban areas contribute significantly to greenhouse gas (GHG) emissions and air pollutants. Particularly, Ho Chi Minh City (HCMC) has the highest vehicle traffic intensity in Vietnam. To improve the traffic system, HCMC has implemented urban railway projects, and this research aims to quantify the co-benefits of these public transport systems. The study used the EMISENS model and the TAMP-EARMOD simulation model system to assess the current situation and to predict the GHG and air pollution emissions when Metro Line 1 (Ben Thanh – Suoi Tien) operates stably. The reduction of air pollution and GHG is calculated to identify the co-benefits when a part of personal transport means is substituted by Metro Line 1. The results show that, if Metro Line 1 is put into operation and reaches 80% of its transport capacity, the air emissions on the route parallel to Metro Line 1 decrease 429.94 tons/year, 13,639.32 tons/year, 11.36 tons/year, 1,137.84 tons/year, 24.27 tons/year for NOx, CO, SO2, NMVOC, and PM2.5, respectively. Importantly, the emission of CO2eq reduces above 49.6 million tons per year, equivalent to 25.4%. Based on these results, the study proposes measures to optimize the deployment of Metro Line 1 to maximize the attainment of co-benefits.