Air Pollution Control Research Articles

Can ecological compensation reduce air pollution? New evidence from resource-based cities in China

ABSTRACT China has made great efforts to establish an ecological compensation mechanism, but there lacks empirical evidence on whether this scheme effectively reduces air pollution. To test the effectiveness of air quality ecological compensation (AQEC) on air pollution control, this study considers 114 resource-based cities in China and uses a multi-period difference-in-difference (DID) model for empirical analysis. The finding shows that the AQEC policy significantly reduces the concentration of air pollutants by promoting air pollution prevention and local authority enthusiasm for pollution abatement, resulting in an average annual decrease in PM2.5 concentrations of approximately 3.9 µg/m3 in the pilot cities. The AQEC policy of resource-based cities in eastern and northern China, and those with less financial pressure have greater inhibitory effects on air pollution. The study recommends establishing long-term protection mechanisms and implementing differentiated policies focused on green technological innovation and financial autonomy.

Enhancement of the Vegetation Carbon Uptake by the Synergistic Approach to Air Pollution Control and Carbon Neutrality in China

Carbon sinks provided by land ecosystems play a crucial role in achieving carbon neutrality. However, the future potential of carbon sequestration remains highly uncertain. The impact of pollutant emission reduction (PER) introduced by the proposed synergistic approach to air pollution control and carbon neutrality on carbon sinks in China has not yet been fully evaluated. In this study, we analyzed the effects of regional carbon-neutral PER policies, global climate change, and their coupled effects on China’s terrestrial gross primary productivity (GPP) by conducting numerical experiments using the weather research and forecasting model coupled with chemistry (WRF-Chem) and the moderate resolution imaging spectroradiometer photosynthesis algorithm (MODIS-PSN). We found that carbon-neutral PER policies could promote GPP growth in most regions of China in 2060, particularly during April and October, resulting in a total increase of at least 21.84 TgC compared to that in 2016, which offset the adverse effects of global climate change up to fourfold. The aerosol radiative effects drive GPP growth under carbon-neutral PER policies, primarily through an increase in daily minimum temperature during winter and an increase in shortwave radiation during other seasons. Our research highlights that reducing pollutant emissions enhances future potential for carbon sequestration, revealing positive feedback towards achieving the target of carbon neutrality.

Variations of source-specific risks for inhalable particles-bound PAHs during long-term air pollution controls in a Chinese megacity: Impact of gas/particle partitioning

Gas/particle (G/P) partitioning is a determining factor that drives the behavior of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere. To comprehend the variations and impacts of PAHs G/P partitioning on inhalation risks from different sources, atmospheric PAHs in Chengdu were studied from January 2009 to January 2021. Chengdu's air quality demonstrated improvement, with a noticeable decline in PM10 (from 238 to 103 μg m−3), PM10-bound PAHs mass concentrations (from 0.08 to 0.01 μg m−3), as well as PAHs inhalation non-cancer (from 63.5 to 7.1) and cancer risks (from 6.2 × 10−5 to 7.7 × 10−6). Decreasing trends were also observed in the concentrations of organic carbon (OC) and the values of absorptive G/P partitioning coefficient (Kp, OM) from 2009 to 2020, indicating a slight decrease in the PM absorptive capacity. A positive matrix factorization (PMF) model utilized three distinct datasets: PMFpp (particle-phase PAHs only), PMFtot (total PAHs concentrations), and PMFpp/gas (particle-phase in parallel with gas-phase PAHs). PMFpp and PMFpp/gas provide reasonable source apportionment and source-specific risk results. However, daily variations in source contributions of PMFtot were found to be unreasonable. PMFpp/gas and PMFtot could identify a source of low molecular weight PAHs (LPAHs) related to temperature, and a significantly positive correlation between LPAHs and temperature was discovered. Gas/particle partitioning of PAHs showed a notable impact on source-specific risks associated with coal and biomass combustion (CC&BC). The findings contribute to our understanding of the variation in PAHs G/P partitioning and the PM absorptive capacity resulting from effective air pollution control in China. Additionally, they offer prerequisite information for incorporating semi-volatile organic compounds in source apportionment and source-specific risk assessment.

Incorporating the Third Law of Geography with Spatial Attention Module–Convolutional Neural Network–Transformer for Fine-Grained Non-Stationary Air Quality Predictive Learning

Accurate air quality prediction is paramount in safeguarding public health and addressing air pollution control. However, previous studies often ignore the geographic similarity among different monitoring stations and face challenges in dynamically capturing different spatial–temporal relationships between stations. To address this, an air quality predictive learning approach incorporating the Third Law of Geography with SAM–CNN–Transformer is proposed. Firstly, the Third Law of Geography is incorporated to fully consider the geographical similarity among stations via a variogram and spatial clustering. Subsequently, a spatial–temporal attention convolutional network that combines the spatial attention module (SAM) with the convolutional neural network (CNN) and Transformer is designed. The SAM is employed to extract spatial–temporal features from the input data. The CNN is utilized to capture local information and relationships among each input feature. The Transformer is applied to capture time dependencies across long-distance time series. Finally, Shapley’s analysis is employed to interpret the model factors. Numerous experiments with two typical air pollutants (PM2.5, PM10) in Haikou City show that the proposed approach has better comprehensive performance than baseline models. The proposed approach offers an effective and practical methodology for fine-grained non-stationary air quality predictive learning.

Diel variations of airborne microbes and antibiotic resistance genes in Response to urban PM2.5 chemical properties during the heating season

Among the components of fine particulate matter (PM2.5), the contributions of airborne microorganisms and antibiotic resistance genes (ARGs) to health risks have been overlooked. Airborne microbial dynamics exhibit a unique diurnal cycle due to environmental influences. However, the specific roles of PM2.5 chemical properties resulting from fossil fuel combustion in driving circadian fluctuations in microbial populations and ARGs remain unclear. This study explored the interactions between toxic components and microbial communities during the heating period to understand the variations in ARGs. Bacterial and fungal communities showed a higher susceptibility to diel variations in PM2.5 compared to their chemical properties. Mantel tests revealed that chemical properties and microbial community interactions contribute differently to ARG variations, both directly and indirectly, during circadian fluctuations. Our findings highlight that, during the daytime, the enrichment of pathogenic microorganisms and ARGs increases the risk of PM2.5 toxicity. Conversely, during the nighttime, the utilization of water-soluble ions by the fungal community increased, leading to a significant increase in fungal biomass. Notably, Aspergillus exhibited a significant correlation with mobile genetic elements and ARGs, implying that this genus is a crucial driver of airborne ARGs. This study provides novel insights into the interplay between the chemical composition, microbial communities, and ARGs in PM, underscoring the urgent need for a comprehensive understanding of effective air pollution control strategies.

An assessment of inorganic components in condensable particulate matter as a function of surface aggregation, spatial suspension state and particle size

Experimental studies assessed the removal efficiency and fine-size distribution of CPM coupled with compositional analysis across air pollution control device systems (APCDs) at an ultra-low emission (ULE) power plant. The findings indicated total CPM emissions were reduced to a minimum of 0.418 mg/m3 at the Wet Electrostatic Precipitator (WESP). The Wet Flue Gas Desulfurization (WFGD) showed the highest removal efficiency (98%) across all particle sizes, notably in the ultra-micron range. Selective Catalytic Reduction (SCR) demonstrated a mere 34% overall efficiency, with a negative removal rate in the ultra-fine particle range. The WESP effectively removed CPM only in sub-micron and ultra-micron sizes, but significantly increased water-soluble ions formation in ultra-fine spatially suspended CPM (CPMspa), leading to overall negative efficiency. Thus, the removal efficiency of the ultra-fine particle range was most affected among the three particle size ranges when the flue gas went through the APCDs. Major metal elements and water-soluble ions were more readily removed by APCDs due to their surface aggregation, while the removal of trace elements like Hg and Se was limited. Reducing SO42-/NH4+ formation in SCR, and optimizing WESP spray system operations based on flue gas components are essential steps in controlling CPM concentration in ULE power plants.

Comprehensive analysis of metal(loid)s and associated metal(loid) resistance genes in atmospheric particulate matter

Despite global concerns about metal(loid)s in atmospheric particulate matter (PM), the presence of metal(loid) resistance genes (MRGs) in PM remains unknown. Therefore, we conducted a comprehensive investigation of the metal(loid)s and associated MRGs in PMs in two seasons (summer and winter) in Xiamen, China. According to the geoaccumulation index (Igeo), most metal(loid)s, except for V and Mn, exhibited enrichment in PM, suggesting potential anthropogenic sources. By employing Positive Matrix Factorization (PMF) model, utilizing a dataset encompassing both total and bioaccessible metal(loid)s, along with backward trajectory simulations, traffic emissions were determined to be the primary potential contributor of metal(loid)s in summer, whereas coal combustion was observed to have a dominant contribution in winter. The major contributor to the carcinogenic risk of metal(loid)s in both summer and winter was predominantly attributed to coal combustion, which serves as the main source of bioaccessible Cr. Bacterial communities within PMs showed lower diversity and network complexity in summer than in winter, with Pseudomonadales being the dominant order. Abundant MRGs, including the As(III) S-adenosylmethionine methyltransferase gene (arsM), Cu(I)-translocating P-type ATPase gene (copA), Zn(II)/Cd(II)/Pb(II)-translocating P-type ATPase gene (zntA), and Zn(II)-translocating P-type ATPase gene (ziaA), were detected within the PMs. Seasonal variations were observed for the metal(loid) concentration, bacterial community structure, and MRG abundance. The bacterial community composition and MRG abundance within PMs were primarily influenced by temperature, rather than metal(loid)s. This research offers novel perspectives on the occurrence of metal(loid)s and MRGs in PMs, thereby contributing to the control of air pollution.

The impact of environmental regulation on firms’ markups: evidence from China

ABSTRACT A comprehensive evaluation of the costs and benefits of environmental regulations provides empirical evidence for policymakers to formulate and introduce environmental policies. Firms’ profitability and competitiveness manifest their market power and provide the micro foundation for economic development and social stability. Therefore, this paper focus on investigating the impact of air pollution environmental regulation on manufacturing firms’ market power, measured by markups, with a difference-in-differences (DID) method. Using air pollution control policy, requiring China’s Key Cities for Air Pollution Control (KCAPC) to meet air quality standards within a specified time limit as a natural experiment, our DID estimations show that air pollution regulation significantly leads to an increase in firms’ markup rate by 0.002 in key cities that did not meet air quality standards. Heterogeneous effects show that this impact is larger for polluting firms, private-owned and foreign-owned firms, and firms located in western and central cities and cities with high marketization. Productivity and market share may be two main influencing channels to explain the positive impact of air pollution environmental regulation on firms’ markups. Our findings suggest that strengthening environmental regulation is conducive to improving the competitiveness and market power of manufacturing firms, lending support to the enforcement of environmental regulations.

Strategies for Prevention and Control of Air Pollution in India at Central Level

Environment pollution has become one of the chief threats to the survival of mankind. India faces severe environmental deterioration. It is a wide reaching problem and it is likely to influenced the great human health. This paper provides the insight view about the affects of air pollution on human beings by diseases, problems and functioning of pollution control board. Various studies found that the every age group is facing life threatening diseases like cancer, asthma etc due to pollution. Various strategies enacted by government from the recent issue of stubble burning to control pollution were to lessen the crop burning which were implemented by government which was not implemented on the serious note. Though the pollution control board plays the successful role to control pollution but still it is increasing day by day.

The short-term effects of individual and mixed ambient air pollutants on suicide mortality: A case-crossover study

It is critical to explore intervenable environmental factors in suicide mortality. Based on 30,688 suicide cases obtained from the Mortality Surveillance System of the Jiangsu Provincial Centre for Disease Control and Prevention, we utilized a case-crossover design, and found that the OR of suicide deaths increased by a maximum of 0.71 % (95 % CI: 0.09 %, 1.32 %), 0.68 % (95 % CI: 0.12 %, 1.25 %), 0.77 % (95 % CI: 0.19 %, 1.37 %), 2.95 % (95 % CI: 1.62 %, 4.29 %), 4.18 % (95 % CI: 1.55 %, 6.88 %), and 0.93 % (95 % CI: 0.10 %, 1.77 %), respectively, for per 10 μg/m3 increase in the particulate matter (PM) with diameters ≤ 2.5 µm (PM2.5), PM with diameters ≤ 10 µm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and per 0.1 mg/m3 increase in carbon monoxide (CO) concentrations with the conditional logistic regression analysis. People living in county-level cities were more susceptible. Particularly, a significant positive association was found between air pollutant mixture exposure and suicide deaths (OR=1.04,95 % CI: 1.01, 1.06). The excess fraction of suicide deaths due to air pollution reached a maximum of 8.07 %. In conclusion, we found associations between individual and mixed ambient air pollutants and suicide deaths, informing the development of integrated air pollution management and targeted measures for suicide prevention and intervention. Environmental ImplicationAs a major contributor to the global burden of disease, air pollution was confirmed by accumulating studies to have adverse impact on mental health, and potentially lead to suicide deaths. However, systematic studies on the association between air pollution and suicide mortality are lacking. We explored the associations of multiple air pollutants and pollution mixtures with suicide deaths and assessed excess suicide mortality due to air pollution, emphasizing the importance of air pollution control on suicide prevention. Our study provides evidence to support mechanistic studies on the association between air pollution and suicide, and informs comprehensive air pollution management.

Monitoring of enteropathogenic Gram-negative bacteria in wastewater treatment plants: a multimethod approach

The wastewater treatment processes are associated with the emission of microbial aerosols, including enteropathogenic bacteria. Their presence in this work environment poses a real threat to the health of employees, both through the possibility of direct inhalation of the contaminated air and indirectly through the pollution of all types of surfaces with such bioaerosol particles. This study aimed to investigate the prevalence of enteropathogenic bacteria in the air, on surfaces, and in wastewater samples collected in four wastewater treatment plants (WWTPs). The effectiveness of conventional culture-biochemical, as well as spectrometric and molecular methods for the rapid detection of enteropathogenic bacteria at workstations related to particular stages of wastewater processing, was also evaluated. Bioaerosol, surface swab, and influent and effluent samples were collected from wastewater plants employing mechanical–biological treatment technologies. The air samples were collected using MAS-100 NT impactor placed at a height of 1.5 m above the floor or ground, simulating aspiration from the human breathing zone. Surface samples were collected with sterile swabs from different surfaces (valves, handles, handrails, and coveyor belts) at workplaces. The raw influent and treated effluent wastewater samples were aseptically collected using sterile bottles. The identification of bacterial entheropathogens was simultaneously conducted using a culture-based method supplemented with biochemical (API) tests, mass-spectrometry (MALDI TOF MS), and molecular (multiplex real-time PCR) methods. This study confirmed the common presence of bacterial pathogens (including enteropathogenic and enterotoxigenic Escherichia coli, Salmonella spp., Campylobacter spp., and Yersinia enterocolitica) in all air, surface, and wastewater samples at studied workplaces. Higher concentrations of enteropathogenic bacteria were observed in the air and on surfaces at workplaces where treatment processes were not hermetized. The results of this study underline that identification of enteropathogenic bacteria in WWTPs is of great importance for the correct risk assessment at workplaces. From the analytical point of view, the control of enteropathogenic bacterial air and surface pollution using rapid multiplex-PCR method should be routinely performed as a part of hygienic quality assessment in WWTPs.

Biogenic volatile organic compounds in forest therapy base: A source of air pollutants or a healthcare function?

Air pollution poses a significant threat to public health, while biogenic volatile organic compounds (BVOCs) play a crucial role in both aspects. However, the unclear relationship between BVOCs and air pollutants in the under-canopy space limits the accuracy of air pollution control and the exploitation of forest healthcare functions. To clarify the variation of BVOCs in forest therapy bases, and their impacts on ozone (O3) and fine particulate matter (PM2.5) at nose height, total VOCs (TVOCs) in the forest were collected during typical sunny days, while air pollutants and meteorological factors were observed simultaneously. The results showed that the branch-level emissions of P. tabuliformis were dominated by healthcare-effective monoterpenoids, with only α-pinene having relative air concentrations of over 5 % in forest air samples. The correlation between concentrations of under-canopy TVOCs and emission rates of BVOCs from P. tabuliformis was weak (p > 0.09) in all seasons. However, the correlation between concentrations of TVOCs and the concentrations of O3 and PM2.5 showed clear seasonal differences. In spring, TVOCs only showed a significant negative correlation with PM2.5 in the forest (p < 0.01). In summer and autumn, TVOCs were significantly negatively correlated with both O3 (p < 0.001) and PM2.5 (p < 0.01). Specifically, the negative linear relationships were more pronounced for O3 and oxygenated VOCs in autumn (R2 = 0.40, p < 0.001) than for other relationships. The relationship between air pollutant concentrations inside and outside the forest also showed significant seasonal differences, generally characterized by a weaker correlation between them during seasons of strong emissions. Therefore, BVOCs in coniferous forests are health functions as they can provide healthcare effects and mitigate the concentration of air pollutants in the forest, and the establishment of forest therapy bases in rural areas with low NOx can be a sensible approach to promote good health, well-being, and sustainable development.

Quantifying US air pollution policy: How political and regional factors influence pollutant mitigation.

Air pollution control in the United States has evolved into a comprehensive policy system spanning from the federal to the state level over time. A unified quantitative analysis of policy intensity can shed light on the policy evolution across different levels, the influence of partisan and regional factors on policy, and the relationships with emissions of major pollutants. By harnessing the policy text of the Clean Air Act (CAA) at the federal level and State Implementation Plans (SIPs) at the state governments (1955-2020), we deployed a Natural Language Processing approach to define a policy intensity index to systematically quantify the US air policy landscape. Our findings highlight that the 1970 CAA amendment carries the most vigorous intensity as it established a holistic control system for the first time. Subsequent years witnessed a general trend of partisan polarization, eventually leading to a graduate convergence between red and blue states. Blue states demonstrated a closer alignment with federal directives and a superior efficacy in pollutant reduction. Regionally, the Northeast displays the highest overall policy intensity, and the West exhibits the highest coordination with the federal benchmarks, making these regions outperform others in air pollution control. Our study not only discusses policy implications for air pollutant reductions considering partisan and regional differences but also provides a novel measurement tool to quantify policies for assessing disparities and synergies.

Development of Measures to Reduce Air Pollutants As Much As Possible

The papers include contemporary ecological challenges, steps taken to reduce artificial pollution, and environmental issues relating to the atmosphere's circulation through natural and artificial processes. A major threat to world health, air pollution can have a range of negative consequences on the environment, such as haze, eutrophication, acid rain, and harm to animals. The combustion of fossil fuels for energy production and transportation is the main cause of air pollution. The effects of air pollution on human health are significant, with millions of people affected by respiratory and cardiovascular diseases, reproductive and central nervous system dysfunctions, and cancer. The articles emphasize the importance of reducing air pollution through various measures, such as improving energy efficiency, promoting renewable energy sources, reducing emissions from transportation, and implementing policies and regulations to control air pollution. The articles also highlight the need for public awareness and a multidisciplinary approach to tackle the problem of air pollution and its impact on climate change and public health.

Determination of Sulphur Dioxide (SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;) Air Emission of Refined Petroleum Products by Emission Factor Approach for Air Pollution Control

Air pollution control is a safe method for achieving a sustainable environment and can be accomplished by adequately monitoring pollutants that pose significant environmental risks. The combustion of sulfur-containing petroleum products has been a major concern for several decades. Therefore, this study was aimed at determining sulfur levels in refined petroleum products such as Premium Motor Spirit (PMS), Automotive Gas Oil (AGO), and Dual-Purpose Kerosene (DPK). It also investigated the air quality implications of sulfur levels and estimated the contribution of the refinery’s products to sulfur dioxide air emission. Fuel samples were collected from the Warri Refining and Petrochemical Company (WRPC) in Nigeria and analyzed using Ultraviolet-visible spectrophotometer (UV-Vis) and Energy-Dispersive X-ray Fluorescence (EDXRF). Sulfur levels were determined at 425 nm wavelength, and sulfur dioxide air emission were estimated for seven consecutive years from 2010 to 2016 using the emission factor approach. The densities of PMS, AGO, and DPK were 0.77 kg/l, 0.832 kg/l, and 0.82 kg/l respectively. The levels of sulfur in PMS, AGO, and DPK were 2.007 x 10&amp;lt;sup&amp;gt;-4&amp;lt;/sup&amp;gt; %, 6.970 x 10&amp;lt;sup&amp;gt;-5&amp;lt;/sup&amp;gt; wt%, and 4.233 x 10&amp;lt;sup&amp;gt;-5&amp;lt;/sup&amp;gt; wt% respectively from UV-Vis technique and 0.016, 0.087 and 0.029% respectively for EDXRF technique were found below the sulfur limit of 0.015 %, 0.005 % and 0.015 % for PMS, AGO and DPK respectively specified by Standard Organization of Nigeria (SON) specifications of 0.1, 0.5 and 0.15wt% for PMS, AGO and DPK respectively. The annual sulfur dioxide emissions were obtained for seven consecutive years from 2010 to 2016. The results from UV-VIS were observed to have the highest SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emission of 0.1718 tons for PMS in 2011, 0.2593 tons in 2010 for AGO, and 0.0974 tons for DPK in 2010, while the lowest emission was observed to be 0.029 tons for PMS in 2015, 0.0362 tons in 2015 for AGO and 0.0181 tons for DPK also in 2015. The results from EDXRF technique were observed to have the highest SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emission of 13.6939 tons for PMS in 2012, 323.6881 tons for AGO in 2010, and 66.7147 tons for DPK also in 2010, while the lowest emissions for PMS, AGO and DPK were all observed in 2015 to be 2.3122, 45.1872, and 12.4182 tons respectively. The study concluded that the refinery complied with the set requirements.

Could environmental regulation effectively boost the synergy level of carbon emission reduction and air pollutants control? Evidence from industrial sector in China

In response to the pressure of combating climate change and enhancing air quality, China has tightened environmental regulations. In China, reducing carbon emissions and air pollutants together has become a critical target for environmental protection. However, no literature explores the impact of environmental regulation on the synergy level of reducing CO2 and air pollutants in the industrial sector. Therefore, this study explores whether environmental regulation could effectively boost the synergy level of carbon emission reduction and air pollutants control in China's industrial sector. We first construct an evaluation indicator system for synergistic emission reduction of CO2 and air pollutants (SO2, NOx, PM), then employs the coupled coordination model to evaluate the synergy level of emission reduction. Furthermore, we explore the impact pathway of environmental regulation on the synergy level of emission reduction. The results indicate that: (1) On the whole, the synergy level shows a slow upward trend, but remains insufficient from 2011 to 2020. (2) Overall, environmental regulation significantly boosts the synergy level of carbon emission reduction and air pollutants control. Regarding the impact pathway, industrial structure has a completely promoting effect, while technical progress exerts a suppressing effect. (3) In regions with higher economic development, environmental regulation has a greater positive influence on synergy level, and the suppressing effect of technical progress is weaker than in less developed regions. These findings could provide helpful references for policy making on synergistic emission reduction of industrial CO2 and air pollutants in China.

Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India

This research was established to accurately forecast daily scale air quality index (AQI) which is an essential environmental index for decision-making. Researchers have projected different types of models and methodologies for AQI forecasting, such as statistical techniques, machine learning (ML), and most recently deep learning (DL) models. The modelling development was adopted for Delhi city, India which is a major city with air pollution issues simialir to entire urban cities of India especially during winter seasons. This research was predicted AQI using different versions of DL models including Long-Short Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM) and Bidirectional Recurrent Neural Networks (Bi-RNN) in addition to Kernel Ridge Regression (KRR). Results indicated that Bi-RNN model consistently outperformed the other models in both training and testing phases, while the KRR model consistently displayed the weakest performance. The outstanding performance of the models development displayed the requirement of adequate data to train the models. The outcomes of the models showed that LSTM, BI-LSTM, KRR had lower performance compared with Bi-RNN models. Statistically, Bi-RNN model attained maximum cofficient of determination (R2 = 0.954) and minimum root mean square error (RMSE = 25.755). The proposed model in this research revealed the robust predictable to provide a valuable base for decision-making in the expansion of combined air pollution anticipation and control policies targeted at addressing composite air pollution problems in the Delhi city.

Trends and drivers of anthropogenic NOx emissions in China since 2020

Nitrogen oxides (NOx), significant contributors to air pollution and climate change, form aerosols and ozone in the atmosphere. Accurate, timely, and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone pollution. However, a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from China—the world's largest emitter—has been lacking since 2020 due to delays in emissions reporting. Here we show a consistent decline in China's NOx emissions from 2020 to 2022, despite increased fossil fuel consumption, utilizing satellite observations as constraints for NOx emission estimates through atmospheric inversion. This reduction is corroborated by data from two independent spaceborne instruments: the TROPOspheric Monitoring Instrument (TROPOMI) and the Ozone Monitoring Instrument (OMI). Notably, a reduction in transport emissions, largely due to the COVID-19 lockdowns, slightly decreased China's NOx emissions in 2020. In subsequent years, 2021 and 2022, reductions in NOx emissions were driven by the industry and transport sectors, influenced by stringent air pollution controls. The satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

Significant changes in the physicochemical properties of BC-containing particles during the cold season in Beijing

The ambient air quality has improved significantly under strict emission controls in Beijing, China over the last decade. Black carbon (BC), as a short-lived climate forcer in ambient aerosols, profoundly impacts the air quality and climate. Previous studies have demonstrated a decline in the mass concentration of BC. In this study, we characterized the chemical compositions and size distributions of BC-containing particles during the cold season of 2022 in Beijing using state-of-the-art instruments capable of exclusively measuring BC-containing particles. The optical properties of BC-containing particles were further calculated based on the Mie theory. Moreover, we compared the properties of BC-containing particles in 2022 with the results of previous studies. The results showed that the diameters of BC cores became larger while the coating thickness of BC-containing particles became thinner in 2022. For the coating materials, the mass fraction of nitrate increased obviously, and even replaced organic matter as the dominant component during the peak of the pollution period. Variations in chemical compositions and size distributions resulted in lower mass absorption cross-sections (MAC) of BC-containing particles from 10.5 ± 1.1 m2/g in 2016 to 7.3 ± 0.8 m2/g in 2022, reduced by 30.5%. Our results demonstrate the synergistic benefits of air pollution control in improving air quality and mitigating climate change. Therefore, the MAC of BC adopted in climate models should vary with the changing air pollution levels. This study emphasizes that it is imperative to conduct long-term observations of BC-containing particles to better estimate BC's climate effects.

Advances in amelioration of air pollution using plants and associated microbes: An outlook on phytoremediation and other plant-based technologies

Globally, air pollution is an unfortunate aftermath of rapid industrialization and urbanization. Although the best strategy is to prevent air pollution, it is not always feasible. This makes it imperative to devise and implement techniques that can clean the air continuously. Plants and microbes have a natural potential to transform or degrade pollutants. Hence, strategies that use this potential of living biomass to remediate air pollution seem to be promising. The simplest future trend can be planting suitable plant-microbe species capable of removing air pollutants like SO2, CO2, CO, NOX and particulate matter (PM) along roadsides and inside the buildings. Established wastewater treatment strategies such as microbial fuel cells (MFC) and constructed wetlands (CW) can be suitably modified to ameliorate air pollution. Green architecture involving green walls and green roofs is facile and aesthetic, providing urban ecosystem services. Certain microbe-based bioreactors such as bioscrubbers and biofilters may be useful in small confined spaces. Several generative models have been developed to assist with planning and managing green spaces in urban locales. The physiological limitations of using living organisms can be circumvent by applying biotechnology and transgenics to improve their potential. This review provides a comprehensive update on not just the plants and associated microbes for the mitigation of air pollution, but also lists the technologies that are available and/or can be modified and used for air pollution control. The article also gives a detailed analysis of this topic in the form of strengths-weaknesses-opportunities-challenges (SWOC). The strategies mentioned in this review would help to attain corporate Environmental Social and Governance (ESG) and Sustainable Development Goals (SDGs), while reducing carbon footprint in the urban scenario. The review aims to emphasise that urbanization is possible while tackling air pollution using facile, green techniques involving plants and associated microbes.