Regional Air Pollution Research Articles

Spatio-Temporal Monitoring and Assessment of Air Quality and its Impact on Public Health from Geospatial perspective over Haryana, India

Abstract. This study aims to evaluate the air quality of the Haryana state, India by utilizing Sentinel-5P satellite data. This study aims to track, quantify, and analyze the level of air pollutants in several regions of Haryana. By integrating and analyzing diverse satellite datasets, the study provides a comprehensive understanding of air quality conditions in the region and supports informed decision-making for pollution mitigation and environmental sustainability. This also examines the public health and environmental impacts of air pollution, identifies pollution sources, reviews existing policies, and also provides recommendations for prevention of air pollution. The outcomes of this study will improve the understanding of air quality dynamics in Haryana and provide preventive measures towards sustainable environmental practices. This paper presents a detailed assessment of air quality in Haryana, India, covering the period from 2019 to 2023 using satellite datasets. This evaluates the concentrations and spatial distributions of air pollutants across Haryana. The experimental results provide significant variations in pollution levels over the four years, with higher concentrations in 2019 and 2021, and lower levels in 2020 and 2023. Moreover, spatial distribution maps illustrate pollutant patterns, emphasizing the temporal and spatial changes in pollution levels. The results also highlight the ongoing challenge of increasing pollution in certain areas of Haryana and the need for continuous monitoring to improve air quality.

A hybrid spatiotemporal model combining graph attention network and gated recurrent unit for regional composite air pollution prediction and collaborative control

Machine learning (ML) models have been extensively applied in air quality prediction. However, many of these models often failed to unveil complex mechanisms and regional spatiotemporal variations of composite air pollution. This brings uncertainties in using ML models for effective composite air pollution control. The present study developed a novel hybrid spatiotemporal model framework combining Graph Attention Network (GAT) and Gated Recurrent Unit (GRU), namely the GAT-GRU model, to foresee composite air pollutions with a focus on PM2.5 and O3. By extracting attention matrices for PM2.5O3 composite pollution and applying the Louvain algorithm, the framework established effective community network divisions for coordinated control of PM2.5O3 composite pollution. The framework was applied and tested in China's “2 + 26″ cities, a city cluster with most heavy PM2.5 and O3 pollution and precursor emission sources. The results demonstrate that the framework successfully captured spatiotemporal evolution of combined PM2.5 and O3 pollution. The attention matrix is autonomously generated during course of the model learning process with the aim to interpret the complex interactions among “2 + 26″ cities. The framework provides a new perspective for the interpretability of artificial intelligence models and offers a methodological support and scientific evidence for formulating regional pollution cooperative governance strategies.

Does administrative division adjustment reduce air pollution? Evidence from city-county mergers in China

Administrative division adjustment plays a crucial role in transforming the spatial layout of cities and effectively contributes to green transformation and high-quality regional economic development. We empirically investigate the impact of administrative division adjustment, exemplified by city-county mergers (CCM), on air pollution using the difference-in-differences method. Our results demonstrate that CCM significantly reduces air pollution, which passes a series of robustness tests including heterogeneous treatment effect tests. Mechanism analysis reveals that CCM reduces air pollution by optimizing industrial structure, promoting market allocation, and constraining government size; geo-climatic conditions significantly moderate the haze reduction effect of CCM. Further analyses indicate that the haze reduction effect of CCM is more pronounced in the eastern and western regions, the southeast regions of the Hu Line, and non-resource-based regions. Moreover, CCM not only alleviates air pollution in border areas and mitigates the pollution boundary effect but also yields the social welfare effect. This paper provides valuable insights for maximizing the haze reduction potential of administrative division adjustment, understanding the role of Chinese-style decentralization in regional air pollution management, especially in border areas, and supporting the achievement of carbon emission reduction and sustainable development goals.

Annual emissions of N2O, NO, HONO, and NH3 from maize-wheat fields in the North China Plain

Fertilized agricultural soil is a significant source of gaseous nitrogen compounds (GNCs), including N2O, NO, HONO, and NH3. The North China Plain (NCP) is the “hot region” for the release of these GNCs due to intensive fertilization practices. However, existing research has primarily focused on N2O emissions from fertilized farmland in the NCP, lacking comprehensive observational studies on other GNCs. Therefore, a continuous cumulative sampling technique (open-top dynamic chamber system) was utilized in this study to simultaneously measure the exchange fluxes of N2O, NO, HONO, and NH3 over summer maize-winter wheat rotation fields in the NCP. Results showed that GNC emissions from the soil displayed distinct diurnal variations, with higher emissions during the day attributed to elevated soil temperature. However, N2O emissions remained consistent between day and night, potentially influenced not only by soil temperature but also by soil humidity. Annual cumulative emissions and emission factors (EFs) for four GNCs were determined, indicating that N2O, NO, and NH3 emissions during the maize season were 1.38–2.37 times higher than those during the wheat season, with 98 % of HONO emissions occurring in the maize season. Additionally, the study first presented the annual HONO EFs of 0.36 ± 0.03 % in fertilized farmland. Furthermore, a comparison revealed that the fluxes of N2O, NO, NH3, and HONO using the conventional single-point sampling method were 26.4 %, 13.9 %, and 8.10 % lower, and 7.86 % higher compared to the continuous cumulative sampling method recommended in this study. In general, this study provided precise measurements of GNC emissions from farmland, offering essential foundational data for modeling parameters and contributing to the formulation of regional air pollution prevention and control policies.

Study on the Precise Evaluation of Environmental Impacts of Air Pollution in Cold Regions Using the Cost Control Method

Objective: With the acceleration of industrialization, air pollution has become a global environmental issue, particularly in cold regions where the unique climatic and geographical conditions give rise to distinctive types of air pollution and impacts. Considering the economic evaluation of environmental damage is crucial for effective pollution control policies, this study aims to provide a more precise environmental damage assessment method through the Improved Virtual Control Cost Method (IVCCM) to optimize air pollution governance strategies in cold regions. Method: This study utilizes a case study of a major company producing methanol and coal-based natural gas, where the emissions from the boiler exhaust exceeded the prescribed standards for particulate matter, sulfur dioxide, and nitrogen oxides during a specific period. By employing a segmented counting approach that accounts for downtime, precise calculations were conducted for the actual periods of excess emissions. Adjustments were made to the calculation coefficients within the Virtual Control Cost Method to more accurately reflect the ecological damage caused by air pollution. Results: The IVCCM calculations revealed that the total environmental loss caused by the company’s excessive air pollution emissions amounted to USD 1.6844 million, significantly lower than the original calculation method (USD 2.1885 million). Specifically, the environmental losses due to particulate matter, sulfur dioxide, and nitrogen oxides were USD 0.0032 million, USD 0.3600 million, and USD 1.3212 million, respectively. Conclusions: The IVCCM enables a more precise assessment and prediction of ecological environmental damage caused by air pollution in cold regions. Compared to traditional methods, it effectively reduces assessment costs, mitigates disputes arising from unclear parameter values and calculation methods, and facilitates the development of more rational environmental protection policies and measures.

The impact of latent policy synergy between cities on air pollution: An empirical analysis from China's 12,764 air policies

Policy synergy plays a crucial role in managing regional air pollution. However, the current process of formulating collaborative policies often focuses too heavily on achieving optimal emission reduction outcomes, while neglecting the execution costs at the local level. This not only leads to a lack of coordination between existing governance measures and new policies but may also result in inefficient policy implementation and the wastage of administrative resources. To address this issue, we have conducted a thorough analysis of the latent interconnections in local governance and explored the possibility of formulating collaborative policies based on latent policy synergies. Utilizing a dataset of 12,764 policy documents from China spanning from 2000 to 2023, we employed unsupervised learning techniques and panel regression models to investigate the impacts of latent policy synergies among local governments. Our findings reveal that local governments initially relied on rigid command-and-control strategies to address air pollution, which were later enhanced with economic incentives like emissions trading and subsidies, thus broadening the scope of policy tools and improving compliance flexibility. Subsequently, as comprehensive monitoring networks were established, enabling real-time data acquisition and more accurate pollution assessments, the focus of policy efforts shifted towards a more integrated approach to regional air pollution management. This similar evolution facilitated latent policy synergy among local governments, leading to significant reductions in air pollution emissions. Notably, regions such as the Central Plains and coastal cities, characterized by their dense industrial activity and high energy consumption, have shown remarkable potential for collaborative efforts, achieving greater pollution control efficiencies. This study provides a valuable reference for the coordinated governance of air pollution policies.

Differentiating hazardous PM2.5 in ambient air of ecologically different districts of India

ABSTRACT Ambient PM2.5 and their toxic components were measured in six ecologically different districts of India. Cadmium (Cd), arsenic (As), chromium (Cr), copper (Cu), zinc (Zn), molybdenum (Mo), and lead (Pb) were present in most of the PM2.5 samples analysed. A new heavy metal exposure index (HEI) was formulated based on weighted geometric mean approach using substance toxicity points given by Agency for Toxic Substance and Disease Registry (ATSDR). The proposed HEI differentiates toxic PM2.5 and helps screen unhealthy air pollution regions, and can thus assist in forming adequate public health policy.

Decoupling Analysis between Socio-Economic Growth and Air Pollution in Key Regions of China

The coordinated development of atmospheric pollution and socio-economic growth plays a core role in the sustainable development of cities and regions. The relationship between socio-economic growth and air pollution can be described using decoupling analysis. The seven key regions of China (168 cities), including Beijing–Tianjin–Hebei and its surrounding areas (BTHSR), the Yangtze River Delta region (YRDR), the Fen-Wei Plain (FWP), the Chengdu–Chongqing region (CCR), the urban agglomeration of the middle reaches of the Yangtze River (MLRYR), the Pearl River Delta region (PRDR), and other provincial capitals and municipalities with specialized plans (OPCCSP) were taken as targets to investigate the spatiotemporal evolution characteristics of AQI values and PM2.5 concentrations from 2014 to 2022. Then, the decoupling relationship between the AQI/PM2.5 and the socio-economic growth index (SEGI) in these key regions was deeply researched by the Tapio decoupling model. The main results were as follows: (1) Although the continuous improvement in air quality was observed in these seven key regions in China, the PM2.5 concentration in the BTHSR and FWP was still higher than 35 μg·m−3. The AQI showed a spatial pattern of high in the north and low in the south, and the distribution of PM2.5 in China was high in the east and low in the west. (2) The decoupling degree between air pollution and socio-economic growth was relatively high in the PRDR and YRDR. In contrast, the degree of decoupling was poor in the FWP and OPCCSP. The decoupling states were primarily influenced by industrial structure, energy consumption, and urbanization. (3) The decoupling of air pollution from socio-economic growth was in a strong decoupling state throughout the majority of the study period, achieving a comparatively ideal decoupling state in 2018. However, the overall decoupling states of the seven regions were not sustainable, and the decoupling stability was relatively poor. During the research period, the decoupling state between socio-economic growth and air pollution changed and was unstable.

Contribution to the study of possible transport of PM10 aerosols in the eastern part of the Czech Republic

The article deals with the assessment of air pollution in the eastern regions of the Czech Republic: Moravia and Silesia, where the limits for the protection of human health for PM and benzo[a]pyrene are significantly exceeded, especially in the north-eastern area. The extent to which this heavily polluted part of Moravia and Silesia affects the central, southern and south-eastern parts of Moravia, i.e. south-eastern part of the Czech Republic, has often been discussed but not proven. The assessment demonstrated the influence and extent of pollutant transport by determining the prevailing daily wind direction. The prevailing NE wind direction results in worse dispersion conditions and higher PM10 concentrations throughout the study area. Conversely, the SW wind direction is a carrier of better dispersion conditions with lower PM10 concentrations in the area. The effect of transport of PM10 pollution in the daily type from the NE direction can be observed at those sites located in the NE of the area of interest from the border with Poland to the Prerov site. In the case of more southerly sites, the methodology used does not allow to determine whether and to what extent they are affected by pollution transport from the northeastern part of Moravia or from neighbouring Poland. This methodology is particularly useful when only 24-h pollutant concentrations are available (not at more detailed, e.g. 1-hour intervals). The internal methodology of the Czech Hydrometeorological Institutefor calculating back trajectories of wind from ground stations is particularly applicable for detecting the origin of short-term episodes with high pollutant concentrations.

Influence of Regional Air Pollution Pressure on the Green Transformation of Higher Education: An Empirical Study Based on PM2.5 in Chinese Cities

Influence of Regional Air Pollution Pressure on the Green Transformation of Higher Education: An Empirical Study Based on PM2.5 in Chinese Cities

Unveiling the health impacts of air pollution transport in China

The transport of atmospheric pollutants plays a pivotal role in regional air pollution, highlighting critical concerns over the unequal health outcomes that arise from such transport. While previous researches predominantly focused on key areas in the battle against air pollution, the intensification of control measures necessitates a national perspective to comprehend the health impacts due to pollution transport. Our study establishes an integrated assessment framework that combine an emission-concentration response surface model with a health impact evaluation model to analyse the nationwide health impacts of PM2.5 and O3 pollution transport across China’s 31 provinces. We found that, interprovincial transport of PM2.5 and O3 contributed to 747,000 and 110,000 deaths respectively in 2017, which amounts to 38% and 48% of deaths caused by total anthropogenic emissions. North, East, and Central China together contribute 82% and 69% to the health impacts caused by regional PM2.5 and O3 transport respectively, and the transport among these three regions is also significant. The analysis of interprovincial health impact transport shows that, for PM2.5, the top contributors are Hebei, Shandong, Henan, Anhui, and Jiangsu, with the most affected being Henan, Shandong, Jiangsu, Hebei, and Guangdong. Regarding O3, Shandong, Hebei, Henan, Jiangsu, and Anhui contribute the most, while Henan, Shandong, Hebei, Jiangsu, and Anhui are the most affected. This study can shed lights on regional control strategies by prioritizing control areas based on the health impact of air pollution transport in China.

Expanded PAH analysis of household air pollution in a rural region of China with high lung cancer incidence

The domestic combustion of locally sourced smoky (bituminous) coal in Xuanwei and Fuyuan counties, China, is responsible for some of the highest lung cancer rates in the world. Recent research has pointed to methylated PAHs (mPAHs), particularly 5-methylchrysene (5MC), within coal combustion products as a driving factor. Here we describe measurements of mPAHs in Xuanwei and Fuyuan derived from controlled burnings (i.e., water boiling tests, WBT, n = 27) representing exposures during stove use, and an exposure assessment (EA) study (n = 116) representing 24 h weighted exposures. Using smoky coal has led to significantly higher concentrations of known and likely human carcinogens than using smokeless coal, including 5MC (3.7 ng/m3 vs. 1.0 ng/m3 for EA samples and 100.8 ng/m3 vs. 2.2 ng/m3 for WBT samples), benzo[a]pyrene (38.0 ng/m3 vs. 7.9 ng/m3 for EA samples and 455.3 ng/m3 vs. 12.0 ng/m3 for WBT samples) and 7,12-dimethylbenz[a]anthracene (1.9 ng/m3 vs. 0.2 ng/m3 for EA samples and 47.7 ng/m3 vs. 0.6 ng/m3 for WBT samples). Mixed effect models for both EA samples and WBT samples revealed clear variation in mPAHs concentrations depending on smoky coal source while stove ventilation was consistently found to reduce measured concentrations (by up to nine fold and 65 fold for EA and WBT samples respectively when using smoky coal). Fuel type had a larger influence on mPAHs concentrations than stove type. These findings indicate that users of smoky coal experience exposure to many PAHs, including known and suspected human carcinogens (especially during cooking activities), many of which are not routinely tested for. Collectively, this provides insights into the potential etiologies of lung cancer in the region and further highlights the importance of targeting clean fuel transitions and stove refinements as the final goal for reducing household air pollution and its associated health risks.

Spatial and temporal variation of PM2.5 and the influence of vegetation in the Yangtze River Delta region

With rapid urbanisation in China, PM2.5 has become a limiting factor for the sustainable development of cities. Taking the Yangtze River Delta as the experimental area, this study analysed the spatial and temporal changes of PM2.5 concentrations from 2001 to 2020. It also examined the variations, dispersion, and correlation with NDVI of PM2.5 concentrations in different vegetation zones at different temporal and spatial scales. The results showed that: (1) The PM2.5 concentration in the Yangtze River Delta showed an overall decreasing trend during 2001–2020, and the change was divided into two phases, starting with an increasing phase and entering a decreasing phase after 2013. (2) In terms of spatial distribution, PM2.5 concentrations in the Yangtze River Delta show a pattern of low in the south and high in the north, with the spatial focus shifting to the north over time. There is a concentration of high levels of particulate matter in the Hefei-Nanjing-Wuxi area. (3) The effect of natural vegetation on the reduction and stabilization of atmospheric particulate matter concentration is better than that of artificial vegetation. (4) Needleleaf forests, broadleaf forests, and shrubs in natural vegetation are more capable of reducing and stabilizing atmospheric particulate matter than grasses. The study can provide a reference for regional air pollution control and regional plant system construction.

Effect of fertilizer deep placement and nitrification inhibitor on N2O, NO, HONO, and NH3 emissions from a maize field in the North China Plain

Fertilized soil is an essential source of atmospheric gaseous nitrogen compounds (GNC, including N2O, NO, HONO, and NH3) that play important roles in global warming and regional air pollution. However, there is still a lack of comprehensive research on the exchange fluxes of these gases between soil and the atmosphere, let alone exploration of mitigation measures. Herein, the fluxes of N2O, NO, HONO, and NH3 under different fertilization treatments (surface fertilization (SF), deep fertilization (DF), DF with added nitrification inhibitor (DN), and control (CK, non-fertilization)) were comparatively investigated by open-top dynamic chambers in a maize field in the North China Plain (NCP) in 2022. The results showed that fertilization significantly promoted soil GNC emissions under SF and DF treatments, while there was no significant increase in GNC emissions except for NH3 under the DN treatment after fertilization. In comparison to the SF treatment, the cumulative emissions under the DF treatment exhibited a significant reduction, amounting to 80.8% for N2O, 89.4% for NO, 88.3% for HONO, 84.8% for NH3, and 83.9% for the total emissions of these four gases. These results emphasize the effect of fertilizer deep placement in mitigating soil GNC emissions, and further reductions were observed when using nitrification inhibitors like dicyandiamide (DCD). Compared with the cumulative emissions under the SF treatment, the DN treatment showed reductions exceeding 95% for N2O, NO, and HONO, and 77.1% for NH3 due to the inhibition of ammonia oxidation by DCD, resulting in an overall reduction of 88.8% for the four gases. Therefore, we advocate deep placement of fertilizer with or without nitrification inhibitors during crop cultivation to achieve a comprehensive reduction in GNC emissions and improve regional air quality.

Driving Factors of NOx Emissions in China: Insights from Spatial Regression Analysis

China’s rapid industrialization and urbanization have led to significant nitrogen oxide (NOx) emissions, contributing to severe atmospheric pollution. Understanding the driving factors behind these emissions is crucial for effective pollution control and environmental management. Therefore, this study is an attempt to provide insights into the influence of socioeconomic factors and explore spatial dependencies of NOx emissions in China in 2022 employing spatial regression models (SRMs). Among the SRMs considered, the spatial Durbin model (SDM) is identified as the most suitable for analyzing regional NOx emissions. The study highlights the importance of controlling electricity consumption and vehicle emissions for addressing air pollution in Chinese regions. Specifically, a one billion kilowatt-hour increase in electricity consumption leads to approximately 549.6 tons of NOx emissions, and an increase of 1000 vehicles in a region results in an average increase of 7113.4 tons of NOx emissions in the same region. Furthermore, per capita consumption expenditure (PCEXP) and research and development (R&D) expenditure exhibit negative direct and spillover impacts. Contrary to previous studies, this research finds that changes in urban population density do not have a significant direct or indirect effect on NOx emissions within the studied areas. Moreover, we conducted additional investigations to assess the effectiveness of government action plans in reducing NOx emissions. Specifically, we evaluated the impact of Phases 1 and 2 of the Clean Air Action Plan, launched in 2013 and 2018, respectively, on the socioeconomic drivers of NOx emissions. Therefore, the data were modeled for the years 2013 and 2017 and compared to the results obtained for 2022. The findings indicate that over the entire period (2013–2022), the emission controls mandated by the action plan resulted in significant reductions in the impact of many of the studied NOx drivers. In conclusion, based on the results, this study presents recommendations to mitigate NOx emissions.

Burden and trends of infectious disease mortality attributed to air pollution, unsafe water, sanitation, and hygiene, and non-optimal temperature globally and in different socio-demographic index regions

BackgroundEnvironmental factors greatly impact infectious disease-related mortality, yet there's a lack of comprehensive global studies on the contemporary burden and trends. This study aims to evaluate the global burden and trends of infectious disease mortality caused by air pollution, unsafe water, poor sanitation, and non-optimal temperature across Socio-Demographic Index (SDI) regions from 1990 to 2019.MethodsThis observational study utilized data from the Global Burden of Diseases Study to examine mortality rates from infectious diseases attributed to environmental risk factors between 1990 and 2019, including air pollution, unsafe water, sanitation, handwashing facilities (UWSH), and non-optimal temperatures. Age-standardized mortality rates (ASMRs) and estimated annual percentage change (EAPC) were utilized to present infectious disease mortality, and its trajectory influenced by environmental risk factors over the years. Nonlinear regression was conducted to explore the association between the SDI and ASMRs across regions from 1990 to 2019.ResultsIn 2019, global infectious disease deaths linked to air pollution, UWSH, and non-optimal temperature reached a startling 2,556,992. Disease mortality varied widely across SDI regions, with the highest number of deaths due to air pollution and UWSH in Low SDI regions, and deaths from non-optimal temperature primarily in High SDI regions. Age disparities emerged, with children under five and the elderly most affected. However, an increasing mortality trend was observed among seniors (65–69, 75–79, and over 80) in High SDI regions due to enteric infections linked to UWSH. Globally, a consistent decrease in ASMR was seen from 1990 to 2019 for all diseases connected to these factors, except for respiratory infections linked to non-optimal temperature.ConclusionsOur study underscores the significant impact of air pollution, UWSH, and non-optimal temperatures on global infectious disease mortality, particularly among vulnerable groups such as children and the elderly. It's important to tackle these challenges with targeted interventions aiming to enhance environmental quality, improve water and sanitation systems, and control extreme temperatures. In addition, international cooperation is essential for bridging regional disparities and driving global public health initiatives forward, thereby helping achieve Sustainable Development Goals more effectively.

Intensification of Mid‐Latitude Cyclone by Aerosol‐Radiation Interaction Increases Transport of Canadian Wildfire Smoke to Northeastern US

AbstractWildfires have long been regarded as one chief culprit in regional air pollution, and pose great impacts on climate change. Although climate forcing of wildfire smoke has been widely investigated, its influence on synoptic systems remains unclear. Based on measurement and modeling analysis, the impact of wildfire smoke on the development of a mid‐latitude cyclone was revealed for Canadian wildfires in early June of 2023. The radiative forcing induced by smoke at surface and in the atmosphere reached up to −150 and 100 W m−2, posing opposite tendencies of atmospheric stratification over the land and ocean. Such perturbations contributed to the enhancement and stagnation of the cyclone, which favored the transport of smoke from the fire‐intensive region, indicated by nearly 40% increment of PM2.5 mass flux. With escalating wildfire risk in the future, the inclusion of smoke aerosols' impacts on meteorology in weather forecast models is of great importance.

Big data analyses for determining the spatio-temporal trends of air pollution due to wildfires in California using Google Earth Engine

California has a long history of wildfires that release substantial amounts of smoke, contributing to regional air pollution. This study employs advancements in Earth observation satellites, cloud computing, and the Google Earth Engine to analyze MODIS MCD19A2 Version 6 level 2, Sentinel-5P NRTI AER AI, and Sentinel-5P NRTI NO2, evaluating the impact of wildfires from 2010 to 2022 on air quality in California. Historical fire events are cross-validated using the MODIS 1-km MYD14A1 V6 dataset, and the MODIS MAIAC-derived Aerosol Optical Depth (AOD) values are validated against AERONET AOD measurements from ground-based sun photometers. To assess the analysis's uncertainty, metrics such as Mean Absolute Error, Relative Mean Bias, and Root Mean Square Error are applied. Additionally, linear regression is used to verify the correlation between satellite and ground measurements. Results show that the average monthly MODIS MAIAC AOD at 470 nm and 550 nm tends to overestimate AOD by 24% and 6%, respectively, compared to AERONET AOD values. The correlation coefficient and adjusted R-squared value range from 0.78 to 0.80 and from 0.61 to 0.65, respectively, for AOD values at 470 nm and 550 nm. During the fire season, correlations exhibit closer associations, with a coefficient above 0.78 and an adjusted R-squared value above 0.63 are observed for both wavelengths. Sentinel-5P data reveal a significant increase in NO2 concentration in the surrounding areas during the 2020 and 2021 wildfires. This study identifies historical spatiotemporal trends of air pollution attributable to wildfires in California from 2010 to 2022, informing decision-making in the development of effective prevention and mitigation programs.

Assessing aerosol-radiation interaction with WRF-chem-solar: Case study on the impact of the “pollution reduction and carbon reduction synergy” policy

Aerosol-radiation interaction (ARI) plays an important role in air quality and climate change. The implementation of the “Pollution Reduction and Carbon Reduction Synergy (PRCRS)” policy provides a great case to explore the impact of ARI on air quality in Beijing and the surrounding Beijing-Tianjin-Hebei (BTH) region. In this study, we analyzed the pollution characteristics and their relationship with meteorological factors in the BTH region, and used the WRF-Chem-Solar model to study the impact of the ARI effect on regional meteorological conditions, air quality improvement, and renewable energy during the implementation of atmospheric pollution improvement policies based on four different scenarios. The ARI effect led to decreases in 2-m temperature, planetary boundary layer height, surface downward shortwave radiation (SWDOWN), and an increase in 2-m relative humidity. The meteorological conditions were unfavorable to the dispersion of pollutants, and the ARI effect can lead to further aggravation of pollutants. The implementation of the PRCRS policy can suppress the adverse effects of ARI on regional air pollution diffusion conditions and improve regional pollution meteorological conditions, and the ARI effect can further enhance the policy's impact on improving air quality. In terms of renewable energy, the implementation of the PRCRS policy will increase renewable energy in the BTH region, due to the inhibition of the ARI effect on SWDOWN and wind speed at 100 m.

Global health benefits of shipping emission reduction in early 2020

The impact of COVID-19 lockdown on the absolute concentration of air pollutant has been widely investigated, whereas the impact of lockdown on global shipping-related air pollutants still remained poorly understood because the contribution of individual source cannot be observed directly. In our study, we employed an efficient chemical transport model (GEOS-Chem) to quantify the shipping-related PM2.5, NO2, and O3 levels in early 2019 and 2020, and assessed the impact of COVID-19 lockdown on global shipping-related air pollutants and health effects. The result suggested that shipping-related global PM2.5, NO2, and O3 levels reduced by 14%, 85%, and 1%, respectively. Furthermore, the decreasing ratios of air pollutants in difference regions often suffered from large spatial discrepancy. PM2.5 and NO2 levels in China, India, Europe, and the United States decreased by 6.5% (NO2: 9%), 7.4% (8%), 11% (8.6%), and 15% (10%), which could be caused by dense shipping activities during the non-lockdown period. For O3 concentrations, the shipping-related concentrations in China, India, Europe, and the United States showed 0.7%, −12.9%, 16.6%, and −4.8% during lockdown period, respectively. The relatively slight O3 reduction might be linked with more significant decrease of NOx emission than VOCs. The changes of air pollutant concentrations inevitably led to the variations of health benefits. Globally, the all-cause mortalities caused by shipping-related PM2.5 exposures reached 40,464 (95% CI: 26,546, 54,382) and 39,035 (95% CI: 25,135, 52,935) cases in early 2019 and 2020, respectively. The combined health benefits of PM2.5, NO2, and O3 linked with shipping emission reduction in China, India, Europe, and the United States reached 476 (95% CI: 131, 822), 3341 (95% CI: 3,177, 3505), 2194 (95% CI: −970, 5358), and 311 (95% CI: 242, 379), respectively. Our study confirms the potentially considerable effects of shipping emission on multiple air pollutants and health impacts, which could provide valuable information for air quality management.