Identifying Driving Factors of Atmospheric N2O5 with Machine Learning.

Dinitrogen pentoxide (N2O5) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of N2O5 formation remains challenging using traditional statistical methods, impeding effective emission control measures to mitigate NOx-induced air pollution. Here, we adopted machine learning assisted by steady-state analysis to elucidate the driving factors of N2O5 before and during the 2022 Winter Olympics (WO) in Beijing. Higher N2O5 concentrations were observed during the WO period compared to the Pre-Winter-Olympics (Pre-WO) period. The machine learning model accurately reproduced ambient N2O5 concentrations and showed that ozone (O3), nitrogen dioxide (NO2), and relative humidity (RH) were the most important driving factors of N2O5. Compared to the Pre-WO period, the variation in trace gases (i.e., NO2 and O3) along with the reduced N2O5 uptake coefficient was the main reason for higher N2O5 levels during the WO period. By predicting N2O5 under various control scenarios of NOx and calculating the nitrate formation potential from N2O5 uptake, we found that the progressive reduction of nitrogen oxides initially increases the nitrate formation potential before further decreasing it. The threshold of NOx was approximately 13 ppbv, below which NOx reduction effectively reduced the level of night-time nitrate formations. These results demonstrate the capacity of machine learning to provide insights into understanding atmospheric nitrogen chemistry and highlight the necessity of more stringent emission control of NOx to mitigate haze pollution.

Association of Gaseous Ambient Air Pollution and Dementia-Related Neuroimaging Markers in the ARIC Cohort, Comparing Exposure Estimation Methods and Confounding by Study Site.

BACKGROUND: Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE: We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS: We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxides (NOx), and 8- and 24-h ozone (O3) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS: Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher NO2 and NOx and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION: Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, NOx, and NO2 and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906.

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas.

Introduction: Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NOx), and sulfur dioxide (SO2), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. Methods: To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Results: Version 1.0 of LOCAETA displays the estimated primary PM2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. Discussion: LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

Exposure to ambient air pollutants during circadian syndrome and subsequent cardiovascular disease and its subtypes and death: A trajectory analysis.

BACKGROUND: The association between exposure to air pollutants and cardiovascular disease (CVD) trajectory in individuals with circadian syndrome remains inconclusive. METHODS: The individual exposure levels of air pollutants, including particulate matter (PM) with aerodynamic diameter ≤ 2.5 µm (PM2.5), PM with aerodynamic diameter ≤ 10 µm (PM10), PM2.5 absorbance, PM with aerodynamic diameter between 2.5 µm and 10 µm, nitrogen dioxide (NO2), nitrogen oxides (NOx), and air pollution score (overall air pollutants exposure), were estimated for 48,850 participants with circadian syndrome from the UK Biobank. Multistate regression models were employed to estimate associations between exposure to air pollutants and trajectories from circadian syndrome to CVD/CVD subtypes (including coronary heart disease [CHD], atrial fibrillation [AF], heart failure [HF], and stroke) and death. Mediation roles of CVD/CVD subtypes in the associations between air pollutants and death were evaluated. RESULTS: After a mean follow-up time over 12 years, 12,570 cases of CVD occurred, including 8192 CHD, 1693 AF, 1085 HF, and 1600 stroke cases. In multistate model, per-interquartile range increment in PM2.5 (hazard ratio: 1.08; 95 % confidence interval: 1.06, 1.10), PM10 (1.04; 1.01, 1.06), PM2.5 absorbance (1.04; 1.02, 1.06), NO2 (1.07; 1.03, 1.11), NOx (1.08; 1.04, 1.12), or air pollution score (1.06; 1.03, 1.08) was associated with trajectory from circadian syndrome to CVD. Significant associations between the above-mentioned air pollutants and trajectories from circadian syndrome and CVD to death were observed. CVD, particularly CHD, significantly mediated the associations of PM2.5, NO2, NOx, and air pollution score with death. CONCLUSIONS: Long-term exposure to air pollutants during circadian syndrome was associated with subsequent CVD and death. CHD emerged as the most prominent CVD subtype in CVD progression driven by exposure to air pollutants during circadian syndrome. Our study highlights the importance of controlling air pollutants exposure and preventing CHD in people with circadian syndrome.

Alder expansion stimulates nitrogen oxide (NOx) emissions from southern Eurasian permafrost peatlands.

Nitrogen oxides (NOx) play an important role for atmospheric chemistry and radiative forcing. However, NOx emissions from the vast northern circumpolar permafrost regions have not been studied in situ due to limitations of measurement techniques. Our goals were to validate the offline analytical technique, and based on this, to widely quantify in situ NOx emissions from peatlands in the southern Eurasian permafrost region. To this end, we conducted a comparison of online and offline flux measurements in 2018 and 2019 using the synthetic air flushing, steady-state opaque chamber method. With differences in annual average and cumulative fluxes less than 0.1 µg N m-2 h-1 and 0.01 kg N ha-1 year-1, the online and offline fluxes were in good agreement, demonstrating the feasibility of conducting offline measurements in remote regions without power supply. The flux measurements over 2 years showed obvious NOx emissions of 0.05-0.14 and 0.13-0.30 kg N ha-1 year-1 in the hollow and hummock microtopography of permafrost peatlands, respectively. The rapid expansion of alder (Alnus sibirica) in the peatlands induced by permafrost degradation significantly increased soil mineral N contents and NOx emissions depending on the age of alder (0.64-1.74 and 1.44-2.20 kg N ha-1 year-1 from the alder forests with tree ages of 1-10 years and 11-20 years, respectively). Alder expansion also intensively altered the thermal state of permafrost including the sharp increases of soil temperatures during the non-growing season from October to April and active layer thickness. This study provides the first in situ evidences of NOx emissions from the northern circumpolar permafrost regions and uncovers the well-documented expansion of alders can substantially stimulate NOx emissions and thus, significantly affect air quality, radiative forcing, and ecosystem productivity in the pristine regions.

Association between air pollution and skin cutaneous melanoma: A Mendelian randomization study.

There has been a consistent and notable increase in the global prevalence of skin cutaneous melanoma (SKCM). Although genetic factors are closely associated with the occurrence and development of melanoma, the potential influence of environmental factors cannot be overlooked. The existing literature lacks a definitive consensus on the correlation between air pollution and the incidence rate of SKCM. This study seeks to investigate the causal relationship between air pollution, specifically focusing on particulate matter (PM) 2.5, PM2.5-10, PM10, and nitrogen oxides, and the risk of SKCM. A 2-sample Mendelian randomization (MR) method was applied, utilizing extensive publicly accessible genome-wide association studies summary datasets within European populations. The primary analytical method employed was the inverse variance weighted method. Supplementary methods, including the weighted median model, MR-Egger, simple model, and weighted model, were chosen to ensure robust analysis. Heterogeneity assessment was conducted using Cochran's Q test. To identify potential pleiotropy, both MR-Egger regression and the MR-PRESSO global test were employed. Additionally, a sensitivity analysis was performed using the leave-one-out method. The analysis revealed no statistically significant association between air pollution and SKCM risk, with specific findings as follows: PM2.5 (P = .485), PM2.5-10 (P = .535), PM10 (P = .136), and nitrogen oxides (P = .745). While some results exhibited heterogeneity, all findings demonstrated an absence of pleiotropy. This study did not find substantive evidence supporting a causal relationship between air pollution and the risk of SKCM within European populations. The comprehensive MR analysis, encompassing various pollutants, suggests that environmental factors such as air pollution may not be significant contributors to the development of SKCM.

Nitroxyl donating and visualization with a coumarin-based fluorescence probe.

Nitroxyl (HNO), the single-electron reduction product of nitric oxide (NO), has attracted great interest in the treatment of congestive heart failure in clinical trials. In this paper, we describe the first coumarin-based compound N-hydroxy-2-oxo-2H-chromene-6-sulfonamide (CD1) as a dualfunctional HNO donor, which can release both an HNO signaling molecule and a fluorescent reporter. Under physiological conditions (pH 7.4 and 37 °C), the CD1 HNO donor can readily decompose with a half-life of ∼90 min. The corresponding stoichiometry HNO from the CD1 donor was confirmed using both Vitamin B12 and phosphine compound traps. In addition to HNO releasing, specifically, the degradation product 2-oxo-2H-chromene-6-sulfinate (CS1) was generated as a fluorescent marker during the decomposition. Therefore, the HNO amount released in situ can be accurately monitored through fluorescence generation. As compared to the CD1 donor, the fluorescence intensity increased by about 4.9-fold. The concentration limit of detection of HNO releasing was determined to be ∼0.13 µM according to the fluorescence generation of CS1 at physiological conditions. Moreover, the bioimaging of the CD1 donor was demonstrated in the cell culture of HeLa cells, where the intracellular fluorescence signals were observed, inferring the site of HNO release. Finally, we anticipate that this novel coumarin-based CD1 donor opens a new platform for exploring the biology of HNO.

Urban air pollution evaluation in downtown streets of a medium-sized Latin American city using AERMOD dispersion model.

The transport sector is considered the largest contributor of air pollutants in urban areas, mainly on-road vehicles, affecting the environment and human health. Bahía Blanca is a medium-sized Latin American city, with high levels of traffic in the downtown area during peak hours. In this regard, it is necessary to analyze air pollution using an air quality model considering that there are no air pollutant measurements in the central area. Furthermore, this type of study has not been carried out in the region and since the city is expected to grow, it is necessary to evaluate the current situation in order to make effective future decisions. In this sense, the AERMOD model (US-EPA version) and the RLINE source type were used in this work. This study analyzes the variations of pollutant concentrations coming from mobile sources in Bahía Blanca's downtown area, particularly carbon monoxide (CO) and nitrogen oxides (NOx) during the period Jul-2020 to Jun-2022. It is interesting to note the results show the maximum concentration values detected are not directly associated with maximum levels of vehicle flow or emission rates, which highlights the importance of meteorological parameters in the modeling. In addition, alternative scenarios are proposed and analyzed from a sustainable approach. Regarding the scenario analysis, it can be concluded that diesel vehicles have a large influence on NOx emissions. Moreover, restrictions as strict as those proposed for a Low Emission Zone would be less applicable in the city than alternative temporary measures that modify traffic at peak hours.

Association of Exposure to Ambient Air Pollutants With Cognitive Performance and Dementia Risk and the Mediating Role of Pulmonary Function: Evidence From the UK Biobank.

BACKGROUND: The pathways by which air pollution affects cognition remain to be explored. This study aimed to explore how single air pollutants [including nitrogen oxide (NOX), nitrogen dioxide (NO2), particulate matter with a diameter of 2.5 micrometers (PM2.5), PM10, and PM2.5-10], and air pollution mixture could affect cognitive function and the incidence of dementia, and determine whether pulmonary function (PF) could play a mediating role in the relationship. METHODS: Multiple statistical methods were employed to evaluate association of 5 air pollutants (NOX, NO2, PM2.5, PM10, and PM2.5-10) with cognitive function. Bootstrap method was used to estimate mediating role of PF in the association of air pollutants with cognition or the incidence of dementia. RESULTS: A mixture of air pollutants was associated with performance on 5 cognitive tests, and global cognition (p < .05). Significantly negative association was also identified between mixture of air pollutants and PF (ß= -0.020, 95% confidence interval (CI) = -0.029 to -0.011). In addition, as PF scores increase, performance on all cognitive tests significantly improve, although the risk of dementia correspondingly decreases. It was noted that PF was shown to mediate the effects of air pollution mixtures on all cognitive tests as well as global cognition. For global cognition, PF mediated 6.08% of the association. PF was also found to have a mediating role in the association between NOX, NO2, PM2.5, and the risk of dementia. CONCLUSIONS: Mixed air pollution may impact cognitive function, with PF potentially mediating this relationship.

A rhodamine-based fluorescent probe used to determine nitroxyl (HNO) in lysosomes.

The reactive nitrogen species (RNS) in lysosomes play a major role during the regulation of lysosomal microenvironment. Nitroxyl (HNO) belongs to active nitrogen species (RNS) and is becoming a potential diagnostic and therapeutic biomarker. However, the complex synthesis routes of HNO in biosystem always hinder the exact determination of HNO in living cells. Here, a rhodamine-based fluorescent probe used to determine nitroxyl (HNO) in lysosomes was constructed and synthesized. 2-(Diphenylphosphino)benzoate was utilized as the sensing unit for HNO and morpholine was chose as the targeting group for lysosome. Before the addition of HNO, the probe displayed a spirolactone structure and almost no fluorescence was found. After the addition of HNO, the probe existed as a conjugated xanthene form and an intense green fluorescence was observed. The fluorescent probe possessed fast response (3 min) and high selectivity for HNO. Furthermore, fluorescence intensity of the probe linearly related with the HNO concentration in the range of 6.0 × 10-8 to 6.0 × 10-5 mol L-1. The detection limit was found to be 1.87 × 10-8 mol L-1 for HNO. Moreover, the probe could selectively targeted lysosome with excellent biocompatibility and had been effectually utilized to recognize exogenous HNO in A549 cells.

Air pollution in Bialowieza forest: Analysis of short-term trends from 2014 to 2021.

Air pollution caused by sulphur dioxide (SO2) and nitrogen oxides (NOx) has negative impacts on forest health and can initiate forest dieback. Long-term monitoring and analysis of these pollution are carried out in Bialowieza Forest in NE Poland due to the threats from abiotic, biotic and anthropogenic factors. The main objective of our study was to monitor the levels and trends of air pollutant deposition in Bialowieza Forest. During a short-term monitoring period over six years (2014-2021), the concentration of SO2 in the air decreased significantly (from 2.03 µg m-3 in December 2015 to 0.20 µg m-3 in July 2016), while the concentration of NO2 in the air showed a non-significant decrease (from 8.24 µg m-3 in December 2015 to 1.61 µg m-3 May 2016). There was no significant linear trend in the wet deposition of S-SO4 anions. Mean monthly S-SO4 deposition varies between 4.54 and 94.14 mg m-2month-1. Wet nitrogen deposition, including oxidized nitrogen (N-NO3) and reduced nitrogen (N-NH4), showed a non-significant increase. Mean monthly precipitation of N-NO3 and N-N H4 ranged from 1.91 to 451.73 mg m-2month-1. Neither did total sulphur deposition nor total nitrogen deposition exceed the mean deposition values for forests in Europe (below 6 ha-1yr-1 and 3-15 ha-1yr-1, respectively). Our results indicate that air pollutants originate from local sources (households), especially from the village of Bialowieza, as demonstrated by the level and spatial distribution of air pollutant deposition. This indicates that air pollutants from the village of Bialowieza could spread to other parts of Bialowieza Forest in the future and may have a negative impact on forest health and can initiate forest dieback. It is therefore important to continue monitoring air pollution to assess the threats to this valuable forest ecosystem.

Estimating regional CO2 and NOx emissions from road transport using real-world data-based emission factors in Korea.

The average-speed emission model (Speed-based model), a widely used and simple method of calculating road vehicle emissions, offers easy accessibility by expressing emissions as a function of average speed. However, there are limitations in expressing emissions generated through complex mechanisms simply as a function of speed. Real-world driving tests using a portable emission measurement system can incorporate the impact of vehicle driving load on emissions. In this study, we analyzed real-world emissions data from 94 light-duty vehicles and developed time-based emission factors depending on vehicle speed and vehicle-specific power (VSP). We also propose a speed-VSP based model to estimate regional CO2 and NOx emissions by combining time-based emission factors and vehicle operating times. The speed-based model and Speed-VSP based model exhibit a 44% difference in NOx emissions and a 29% difference in CO2 emission. In a comparison of the two models against RDE test results, the speed-VSP based model achieved high accuracy in predicting NOx and CO2 emissions with a lower root mean square error (RMSE). Specifically, for NOx emissions predictions, the speed-VSP based model achieved an RMSE of 122-270 mg/km, while the speed-based model showed a much higher RMSE of 435-476 mg/km. For CO2 emissions predictions, the speed-VSP based model achieved an RMSE of 34-56 mg/km, while the speed-based model showed a much higher RMSE of 36-72 mg/km. The results of this study present an opportunity to reassess and improve conventional method of measuring and evaluating emissions from road transport.

Experimental assessment of pollutant emissions from residential fuel cells and comparative benchmark analysis.

Energy transition currently brings focus on fuel cell micro-combined heat and power (mCHP) systems for residential uses. The two main technologies already commercialized are the Proton Exchange Membrane Fuel Cells (PEMFCs) and Solid Oxide Fuel Cells (SOFCs). The pollutant emissions of one system of each technology have been tested with a portable probe both in laboratory and field-test configurations. In this paper, the nitrogen oxides (NOx), sulphur dioxide (SO2), and carbon monoxide (CO) emission levels are compared to other combustion technologies such as a recent Euro 6 diesel automotive vehicle, a classical gas condensing boiler, and a gas absorption heat pump. At last, a method of converting the concentration of pollutants (in ppm) measured by the sensors into pollutant intensity per unit of energy (in mg/kWh) is documented and reported. This allows for comparing the pollutant emissions levels with relevant literature, especially other studies conducted with other measuring sensors. Both tested residential fuel cell technologies fed by natural gas can be considered clean regarding SO2 and NOx emissions. The CO emissions can be considered quite low for the tested SOFC and even nil for the tested PEMFC. The biggest issue of natural gas fuel cell technologies still lies in the carbon dioxide (CO2) emissions associated with the fossil fuel they consume. The gas absorption heat pump however shows worse NOx and CO levels than the classical gas condensing boiler. At last, this study illustrates that the high level of hybridization between a fuel cell and a gas boiler may be responsible for unexpected ON/OFF cycling behaviours and therefore prevent both sub-systems from operating as optimally and reliably as they would have as standalone units.

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control.

This study presents the measurement of photochemical precursors during the lockdown period from January 23, 2020, to March 14, 2020, in Chengdu in response to the coronavirus (COVID-19) pandemic. To derive the lockdown impact on air quality, the observations are compared to the equivalent periods in the last 2 years. An observation-based model is used to investigate the atmospheric oxidation capacity change during lockdown. OH, HO2, and RO2 concentrations are simulated, which are elevated by 42, 220, and 277%, respectively, during the lockdown period, mainly due to the reduction in nitrogen oxides (NOx). However, the radical turnover rates, i.e., OH oxidation rate L(OH) and local ozone production rate P(O3), which determine the secondary intermediates formation and O3 formation, only increase by 24 and 48%, respectively. Therefore, the oxidation capacity increases slightly during lockdown, which is partly attributed to unchanged alkene concentrations. During the lockdown, alkene ozonolysis seems to be a significant radical primary source due to the elevated O3 concentrations. This unique data set during the lockdown period highlights the importance of controlling alkene emission to mitigate secondary pollution formation in Chengdu and may also be applicable in other regions of China given an expected NOx reduction due to the rapid transformation to electrified fleets in the future.

Ambient air pollution, lifestyle, and genetic predisposition on all-cause and cause-specific mortality: A prospective cohort study.

BACKGROUND: Although it is widely acknowledged that long-term exposure to ambient air pollution is closely related to the risk of mortality, there were inconsistencies in terms of cause-specific mortality and it is still unknown whether lifestyle and genetic susceptibility could modify the association. METHODS: This population-based prospective cohort study involved 461,112 participants from the UK Biobank. The land-use regression model was used to estimate the concentrations of particulate matter (PM2.5, PMcoarse, PM10), and nitrogen oxides (NO2 and NOx). The association between air pollution and mortality was evaluated using Cox proportional hazard models. Furthermore, a lifestyle score incorporated with smoking status, physical activity, alcohol consumption, and diet behaviors, and polygenic risk score using 12 genetic variants, were developed to assess the modifying effect of air pollution on mortality outcomes. RESULTS: During a median follow-up of 14.0 years, 33,903 deaths were recorded, including 17,083 (2835; 14,248), 6970, 2429, and 1287 deaths due to cancer (lung cancer, non-lung cancer), cardiovascular disease (CVD), respiratory and digestive disease, respectively. Each interquartile range (IQR) increase in PM2.5, NO2 and NOx was associated with 7 %, 6 % and 5 % higher risk of all-cause mortality, respectively. Specifically, for cause-specific mortality, each IQR increase in PM2.5, NO2 and NOx was also linked to mortality due to cancer (lung cancer and non-lung cancer), CVD, respiratory and digestive disease. Furthermore, additive and multiplicative interactions were identified between high ambient air pollution and unhealthy lifestyle on mortality. In addition, associations between air pollution and mortality were modified by lifestyle behaviors. CONCLUSION: Long-term exposure to air pollutants increased the risk of all-cause and cause-specific mortality, which was modified by lifestyle behaviors. In addition, we also revealed a synergistically detrimental effect between air pollution and an unhealthy lifestyle, suggesting the significance of joint air pollution management and adherence to a healthy lifestyle on public health.

Hydrothermal-enhanced pyrolysis for efficient NOX reduction and biochar valorization from food waste digestate.

Pyrolysis has emerged as a promising technology for valorizing digestate resulting from the anaerobic digestion of food waste. However, the high NOX emissions during pyrolysis limit its application. This study proposed a hydrothermal coupled pyrolysis process to control the element transfer in digestate during biochar production. The efficient reduction of NOX emissions and the improvement of biochar adsorbability were realized. The hydrothermal process reduced the nitrogen content in solid digestate by 49.10 %-81.79 %, thus reducing the NOX precursors in syngas and the N-containing substances in bio-oil. Additionally, the specific surface area and the total pore volume of biochar were enhanced from 25 m2/g to 60-73 m2/g and 0.06 cm3/g to 0.12-0.14 cm3/g, respectively. More defects, oxygen-containing functional groups, and doped Ca on the biochar resulted in a high phosphate removal efficiency of 94 %. The proposed technology provides an efficient and environmentally friendly way to utilize the digestate.

Mitigating air pollution benefits multiple sustainable development goals in China.

Achieving the United nations 2030 Sustainable Development Goals (SDGs) remains a significant challenge, necessitating urgent and prioritized strategies. Among the various challenges, air pollution continues to pose one of the most substantial threats to the SDGs due to its widespread adverse effects on human health and ecosystems. However, the connections between air pollution and the SDGs have often been overlooked. This study reveals that out of the 169 SDG targets, 71 are adversely impacted by air pollution, while only 6 show potential positive effects. In China, two major atmospheric nitrogen pollutants, ammonia and nitrogen oxides, resulted in an economic loss of 400 billion United States Dollar (USD) in 2020, which could be reduced by 33% and 34% by 2030, respectively. It would enhance the progress towards SDGs in China by 14%, directly contributing to the achievement of SDGs 1 to 6 and 11 to 15. This improvement is estimated to yield overall benefits totaling 119 billion USD, exceeded the total implementation cost of 82 billion USD with ammonia as the preferential mitigation target. This study underscores the importance of robust scientific evidence in integrated policies aimed at aligning improvements in environmental quality with the priorities of sustainable development.

Evaluation of laboratory and environmental exposure systems for protein modification upon gas pollutants and environmental factors.

Chemical modifications of proteins induced by ambient ozone (O3) and nitrogen oxides (NOx) are of public health concerns due to their potential to trigger respiratory diseases. The laboratory and environmental exposure systems have been widely used to investigate their relevant mechanism in the atmosphere. Using bovine serum albumin (BSA) as a model protein, we evaluated the two systems and aimed to reduce the uncertainties of both the reactants and products in the corresponding kinetic study. In the laboratory simulation system, the generated gaseous pollutants showed negligible losses. Ten layers of BSA were coated on the flow tube with protein extraction recovery of 87.4%. For environmental exposure experiment, quartz fiber filter was selected as the upper filter with low gaseous O3 (8.0%) and NO2 (1.7%) losses, and cellulose acetate filter was appropriate for the lower filter with protein extraction efficiency of 95.2%. The protein degradation process was observed without the exposure to atmospheric oxidants and contributed to the loss of protein monomer mass fractions, while environmental factors (e.g., molecular oxygen and ultraviolet) may cause greater protein monomer losses. Based on the evaluation, the study exemplarily applied the two systems to protein modification and both showed that O3 promotes the protein oligomerization and nitration, while increased temperature can accelerate the oligomerization and increased relative humidity can inhibit the nitration in the environmental exposure samples. The developed laboratory and environmental systems are suitable for studying protein modifications formed under different atmospheric conditions. A combination of the two will further reveal the actual mechanism of protein modifications.

Improving photochemical indicators for attributing ozone sensitivities in source apportionment analysis.

Comprehensive Air Quality Model with extensions (CAMx)-Decoupled Direct Method (DDM) simulations of first-order ozone (O3) sensitivity to nitrogen oxides (NOx) and volatile organic compounds (VOCs) emissions were performed and combined with modelled [Formula: see text] ratios to obtain a range of thresholds for determining O3-sensitivity regimes for different areas of China. Utilising the new threshold ranges for photochemical indicators, the method for determining O3 formation in the Ozone Source Apportionment Technology (OSAT) module within CAMx was improved by a dynamically varied threshold of [Formula: see text] ratio. The O3 concentration contributions in the newly added transition regime were apportioned to NOx and VOCs emissions in proportion to the relationship between the [Formula: see text] ratio and first-order O3 sensitivity. The source contributions of O3 concentrations from different emission sectors from June to September 2019 were compared using the original and improved CAMx-OSAT. The results showed that the O3 concentration contributions changed significantly in the NOx-limited regime, with a maximum decrease of 21.89%, while the contributions increased by up to 7.57% in the VOC-limited regime, and were within 15 µg/m3 in the transition regime. The modified OSAT module enabled a more sophisticated attribution of O3 to precursor emissions and may have far-reaching implications for informing O3 pollution control policy.

Deseasonalized trend of ground-level ozone and its precursors in an industrial city Kaohsiung, Taiwan.

Mitigating ground-level ozone (GLO) remains challenging due to its highly nonlinear formation process. Thus, understanding GLO pollution trends is crucial for developing effective control strategies, especially Kaohsiung industrial city, Taiwan. Based on the long-term monitoring data set of 2011-2022, temporal analysis reveals that monthly mean GLO peaks in autumn (40.66 ± 5.10 ppb), carbon monoxide (CO) and major precursors such as nitrogen oxides (NOx), nonmethane hydrocarbons (NMHC) reach their highest levels in winter. The distinct seasonal variation of air pollutants in Kaohsiung is primarily influenced by the unique blocking effect of the mountainous area under the northeasterly wind, as the city is situated downwind, causing high GLO levels during autumn due to the accumulation of stagnant air hindering the dispersion of pollutants. Over the 12 years (2011-2022), the deseasonalized trend analysis was conducted with p < 0.001, revealing a stabilization trend of GLO (+0.04 ppb/yr) from a previous sharp increase. The observed improvement is credited to a drastic decrease in total oxidants (Ox) at -0.63 ppb/yr due to significantly reducing their precursors. Furthermore, the effectiveness of precursor reduction is also supported by GLO daily maximum profile changes. While high GLO events (>120 ppb) decrease, days within midrange (60-80 ppb) rise from 24.4% to 33.3%. A notable difference emerges when comparing daytime and nighttime GLO. While daytime GLO decreased at -0.22 ppb/yr, nighttime GLO increased at +0.34 ppb/yr. Weakened nocturnal titration effects accounted for the nighttime increase. The distinct spatial variations in GLO trends on a citywide scale underscore that areas with complicated industrial activities may not benefit from a continuing reduction of precursors compared to less-polluted areas. The findings of this study hold significant implications for improving GLO control strategies in heavily industrialized city and provide valuable information to the general public about the current state of GLO pollution.