PM Emissions Research Articles

A comprehensive approach for calibrating anthropogenic effects on atmosphere degradation

Climate change is the most pervasive threat to the ecosystem, species survival, global economy, and urban lives. Global citizens and governments have perceived the alleviation of harmful anthropogenic effects as an urgent priority. However, conflicting interests between interest groups preclude achieving a common goal. The convincing solutions fundamentally proceed from the precise calibration. Considerable efforts have established calibration models where population density and road transportation have been investigated as major proxies. The model components generally involve spatiotemporal characteristics, but the consideration of time-varying, spatially correlated attributes is insufficient. This article presents a pilot approach in a comprehensive manner; it includes a spatial feature transformation procedure called Kriging for spatial consistency and applying model-fitting and explanation techniques. In the case study, the regression models fit by OLS, Ridge, and Lasso showed analogous coefficients for SO2, NO2, CO, O3, PM2.5, and PM10 emissions, whereas the magnitudes and directions extracted by classification techniques such as ANN and XGBoost vary with emission intensity. This quantitative interpretation based on coefficients or weights could be incompatible with qualitative aspects. As an alternative, this article applied SHAP technique to XGBoost so that the discovery of multidirectional relationships complemented this incongruity. In conclusion, the model design needs to encompass the whole process from recognizing data properties to eliciting high accuracy and scientific proof for efficacious policies and schemes. Environmental action building on valid models would promise to alleviate climate risks and sustain lives.

Past and recent changes in the pollution characteristics of PM10 and SO2 in the largest industrial city in South Korea

PM10 and SO2 are major air pollutants in Ulsan, the largest industrial city in South Korea. The purpose of this study was to evaluate the effectiveness of pollution reduction policies by comparing the pollution characteristics of PM10 and SO2 between 2012 and 2020. The concentrations of PM10 and SO2 have substantially decreased over time. Local industry was the primary driver of SO2 levels, whereas various sources were associated with PM10 levels. In 2012 and 2020, the spatial distributions of SO2 were similar, with hot spots around petrochemical and nonferrous industrial complexes, whereas the sources of PM10 differed between the two years. Although industrial emissions of PM10 decreased from 2012 to 2020, the concentrations derived from an air dispersion model were slightly higher in 2020 due to changes in both wind patterns and the strength of the emission sources. In contrast, modeled SO2 levels were higher in 2012 than in 2020 due to greater emissions in 2012. Eastern and northeastern China were identified as potential source areas for the long-range atmospheric transport of both PM10 and SO2, though its influence was significantly lower in 2020. A comparison of the PM10 and SO2 concentrations predicted by a random forest model and the measured concentrations indicates that government policies have been effective in reducing the emissions and ambient air concentrations of both pollutants. In conclusion, this study demonstrates that local industry remains a significant contributor to air pollution in Ulsan despite the effects of governmental policy. Furthermore, as the influence of external sources weakens, there is a pressing need to strengthen the management of local sources to effectively mitigate air pollution in Ulsan.

Modelling the dispersion of particulate matter (PM10) via wind erosion from opencast mining-Moldova Nouă tailings ponds, Romania.

Historically, Romania is known as a mining site of mineral substances, including gold, silver, copper, lead, zin, uranium, manganese, salt, and coal, whereby their long periods of exploitation and extraction affected human health and the environment in various ways. In Moldova Nouă southwest region of Romania, we investigated the environmental impacts of mining activities on air quality over 2021. We quantified PM10 emission rates through in situ monitoring, dispersion modelling, and horizontal and vertical fluxes. Statistical metrics, including the fraction within factor 2 (FAC2), mean bias (MB), mean gross error (MGE), normalized mean bias (NMB), normalized mean gross error (NMGE), coefficient of efficiency (COE), index of agreements (IOAs), and Taylor diagram signifying standards deviation (SD), root mean squared error (RMSE), and correlation coefficient (R), were used to evaluate the reliability of modelling results against observation. Results conclude that PM10 dispersion agrees with MB, MGE, NMB, NMGE, COE, IOA, and Taylor diagram and moderately with FAC2 metrics. PM10 hotspot was investigated in the vicinity of the tailings ponds of 115.5µgm-3 annual mean, 563.7µgm-3 daily mean, 63.3µgm-2s-1 annual horizontal flux, and 3.0µgm-2s-1 annual vertical flux. PM10 dispersion was identified to expand to Moldova Nouă City and nearby country Serbia. Findings concluded that a windy air mass accumulation across the overburdened dumps and ponds causes the increase of PM10 in the air, resulting in the region's pollution. Therefore, results recommend adopting a strategic mitigation measure for residents, policymakers, stakeholders, and urban planners.

The effect of biogas and dimethyl ether on the thermal characteristics of a dual‐fuel diesel engine: A numerical study

AbstractThis investigation used the Diesel‐RK simulation program to carry out a numerical analysis of the effects that dual‐fuel mixes have on the combustion, performance, and emissions of a dual‐fuel diesel engine. It applied the multizone combustion model, and the controlling equations were solved for each individual combustion region. The engine characteristics were examined under the following scenario: it was initially powered by single‐fuel regular diesel (DF), then it switched to dual‐fuel use with 20% biogas, and then it was changed again with the use of 30% dimethyl ether (DME). On this basis, the mentioned biogas and DME ratios were used. The results showed that combustion pressure for the operation of 30% DME and 20% biogas was reduced by 2.45% and 9.57%, respectively, with respect to diesel fuel alone. The Sauter mean diameter (SMD) of the droplets was reduced by 12.6% for 30% DME and 16.2% for 20% biogas. Heat release and brake thermal efficacy (BTE) were reduced slightly with the use of biogas or DME in comparison with DF. The brake‐specific fuel consumption (BSFC) increased by 15.27% and 8.34%, with 30% DME and 20% biogas respectively due to the difference in the energy content of the tested fuels. Nitrogen oxide emissions decreased by 2% and 28% for the operation of 30% DME and 20% biogas, respectively. The summary emission equation (SE), which describes the combination of NOx and PM emissions, decreased by 4.23% and 5.40% with 30% DME and 20% biogas respectively. Based on the results, this paper recommends the use of 20% biogas with diesel rather than 30% DME. The current findings matched well with other scientists' results.

DUST DIFFUSION IN LARGE-SCALE URBAN CONSTRUCTION COMBINING WRF AND CALPUFF MODEL—TAKE XIAMEN AS AN EXAMPLE

With the increasing number of construction sites in cities, construction dust, as one of the essential factors affecting the atmospheric environment, urgently needs more attention. Most existing studies have studied construction dust and other particle sources comprehensively. There remains a need for research on large-scale diffusion ultimately aiming at construction dust, especially studies on the diffusion law of dust generated only by construction dust at a large-scale city level where all construction sites within the city working at the same time. To systematically explore the diffusion distribution of construction dust in such a situation, this paper takes Xiamen as the research object and puts forward a large-scale construction dust diffusion research method by integrating emission factors and combining WRF and CALPUFF model. The spatial distribution of PM10 emission during the simultaneous construction of all sites in Xiamen in 2019 was simulated. The diffusion law of dust in large-scale construction in Xiamen is obtained. On this basis, the regional contribution of construction dust PM10 in various districts of Xiamen and the best start month of each district are obtained, which provides valuable suggestions for government construction control. This research method can be effectively applied to cities similar to Xiamen.

Geographical approach analysis of the impact of air pollution on newborn intrauterine growth and cord blood DNA damage in Mexico City

Abstract Background Few epidemiologic studies have focused on the specific source of ambient air pollution and adverse health effects in early life. Here, we investigated whether air pollutants from different emission sources were associated with decreased birth anthropometry parameters and increased DNA adduct formation in mother-child pairs residing in the Mexico City Metropolitan Area (MCMA). Methods This cross-sectional study included 190 pregnant women recruited during their last trimester of pregnancy from two hospitals at MCMA, and a Modeling Emissions Inventory (MEI) to calculate exposure to ambient air pollutants from different emissions sources (area, point, mobile, and natural) for two geographical buffers 250 and 750 m radii around the participants households. Results Contaminants were positively correlated with umbilical cord blood (UCB) adducts, but not with maternal blood (MB) adducts. PM10 emissions (area and point sources, overall emissions), PM2.5 (point sources), volatile organic compounds (VOC), total organic compounds (TOC) from point sources were positively correlated with UCB adducts. Air pollutants emitted from natural sources were correlated with a decrease in MB and UCB adducts. PM10 and PM2.5 were correlated (p < 0.05) with a decrease in birth weight (BW), birth length (BL) and gestational age at term (GA). In multivariate analyses adjusted for potential confounders, PM10 was associated with an increase in UCB adducts. PM10 and PM2.5 from overall emissions were associated with a decrease in BW, BL and GA at term. Impact Results suggested higher susceptibility of newborns compared to mothers to damage related to ambient air pollution. PMs are associated with birth anthropometry parameters and DNA damage in adjusted models, highlighting the need for more strict regulation of PM emissions.

Dynamometric Investigation on Airborne Particulate Matter from Automobile Brake: Impact of Disc Materials on Brake Emission Factor

In this work, we evaluated the impact of disc rotors of gray cast iron (GCI), nitrocarburized (NC), and superhard ceramic-coated (SCC) GCI on the brake wear PM emissions of passenger vehicles using dynamometric measurements. The brake emission factor (BEF) of the SCC was greatly reduced by more than a factor of 1/5 compared with those for the GCI and NC for both low-steel and non-steel friction materials. Surface topological and microstructural analyses confirmed that more severe wear was pronounced for the NC rotor compared with the SCC, as evidenced by large concave pits in the wear tracks. Analysis of the size-classified airborne PM suggests that reduced micron-sized particles, which originated from the GCI disc, were responsible for the lower BEF due to the increased hardness of the SCC.

Incorporating of TiO2 with oxygenated fuel and post-injection strategy in CRDI diesel engine equipped with EGR: A step towards lower NOX, PM and enhance soot oxidation reactivity

A mixture of diesel, biodiesel (from algae), and butanol was mixed with nano-titanium dioxide at 50 and 100 parts per million in this study under post-injection (PI) strategy and two rates (10 % and 20 %) of exhaust gas recirculation (EGR). In the literature, few studies have investigated how PI strategies effect on engine emissions and combustion performance from mixture of B16M20 by butanol (16 %), microalgae biodiesel (15 %) and diesel with variable EGR rates. To gain a better understanding of the effects of EGR rates on diesel engines running with B16M20 mixture, this study was conducted. The final fuel type test used B16M20 treated with 50 ppm and 100 ppm of nano-TiO2. Fuel specific fuel consumption (BSFC) increased by 3 % for both diesel and B16M20 when EGR was used, but PI reversed this trend. Nanoparticles added to B16M20 blend significantly contributing in decreased BSFC to 6.47 %. 100 ppm nano-TiO2 added to 10 % of EGR, along with PI, can achieve the same or enhance better brake thermal efficiency (BTE) by 4.53 % than pure diesel. The lowest NOX levels by 26.48 % were achieved with 100 ppm nano-TO2 and B16M20 with 20 % EGR. Because of EGR's high heat capacity and dilution effect, higher EGR rates result in higher soot levels. As a result of the PI strategy, the soot levels emitted from B16M20 reduced by 28.57 % compared with diesel fuel. At PI strategy presence (W PI) and adding 100 ppm nano-TiO2 into the B16M20 blend resulted in the lowest PM concentrations by 59 % compared to the diesel and without PI (W/O PI). PM emissions were significantly reduced at temperatures below 600 °C from B16M20 blend combustion with delay injection, 10 % EGR, and 100 ppm nano-TiO2. Soot oxidation was minimized through EGR, and enhanced by nano-TiO2. Adding this 100 ppm of nanoparticles to diesel fuel produced more reactive soot than diesel fuel alone.

PM10 emissions from co-combustion of water washed sea rice waste with coal

Sea rice is a variety of salt-tolerant rice that absorbs significant quantities of Na, K and Cl. This work investigated effects of water washing pretreatment on sea rice waste properties, such as combustion characteristics, particulate matters (PM) emission and PM10 reduction, during its co-combustion with coal. Fuel characterizations, thermogravimetric analyses, ash fusion temperature (AFT) measurements and PM10 collection experiments were performed. A drop tube furnace was used to burn biomass and blended fuel samples at 1500 °C for PM10 collection. The results show that water washing effectively removed undesirable elements, including K, Na, and Cl. The washing pretreatment increased the AFTs of sea rice straw and ordinary rice straw, but had no effect on the husk. The washing delayed the devolatilization of sea rice waste, as did the char combustion. The yield of PM1 from the washed biomass was significantly reduced owing to the extraction of alkali metals and Cl. During co-combustion with coal, the ash particles of biomass could capture the alkali sulfides from coal, which inhibited the formation of PM1. Ca-containing particles in coal could melt and adhere to the large ash particles from the biomass to grow into larger particles, reducing the yield of PM1–10.

Analysis of emission evolution and synergistic reduction effect of air pollutants and CO2 from Chinese coal-fired power plants

The coal-fired power industry is the largest coal-consuming sector in China, and it serves as a significant source of air pollutants and carbon emissions. In this study, we investigated the evolution of air pollutants and CO2 emissions originating from coal-fired power plants (CFPPs) from 2013 to 2020 based on a unit-based bottom-up inventory, and then we quantitatively assessed their combined reduction effects from 2013 to 2060. Our findings indicated that air pollutant emissions experienced a rapid decrease from 2013 to 2020, with nearly 46.0%–64.2% of the reduction occurring within the years 2013–2017. However, CO2 emissions displayed a slight increase during the same period. The top five provinces with the most robust synergistic reduction effects for both air pollutants and CO2 were Jiangsu, Hebei, Henan, Shanxi, and Shandong. The primary measures to the reduction in CO2 emissions were energy structure adjustment and energy conservation and consumption reduction. By 2060, emissions of PM2.5, SO2, NOx, Hg, and CO2 had decreased by 57.9–92.1%, 26.0–80.6%, 18.1–69.4%, 26.6–86.3%, and 35.8–76.1% compared to the levels in 2020, respectively. As the emission reduction process advanced, the reduction effect on CO2 became more pronounced within the synergistic process. We believe that our highly detailed emission inventory comprehensively captures the historical evolution of PM2.5, SO2, NOx, Hg, and CO2 emissions from CFPPs. Furthermore, the scenario analysis results we have obtained will be instrumental in supporting policy development aimed at achieving the synergistic reduction of air pollutants and carbon emissions.

PIXE analysis of contaminants in tree rings in proximity of the aluminum processing factory in Ladomerská Vieska (Slovakia)

The aluminum smelter in the Žiar nad Hronom region of central Slovakia was a substantial source of pollution in the past. Five trees were sampled in close proximity to the smelter and the tree rings were chemically processed and analyzed with the PIXE technique. Elevated concentrations of Mg, Al, Si, P, S, K, Ca, Fe, and Zn were observed in tree rings, however, they did not show a significant correlation with PM, HF and SO2 emission rates. Concentration trends show a significant effect of the heartwood-sapwood boundary layer, where a substantial drop or increase was observed between tree-ring sections.

Study on particulate emission in two-lane mixed traffic flow

In order to study the emission of particulate matter in traffic flow composed of long and short vehicles, a two-lane cellular automaton (CA) model with mixed traffic flow is proposed based on Braking-Light(BL) CA model and the measured pollutant emission formula, in which the mixing ratio is introduced to allocate the long and short vehicles on the road. Numerical simulations are performed to study the emission of particulate matter in the mixed traffic flow under symmetric and asymmetric lane-changing rules. When the mixing ratio of the system is constant, the different mixing ratios in both lanes at the initial moment have little influence on the traffic current. Under the symmetric lane-changing rule, the lane exchange rate of vehicles reaches its peak in free flow areas, whereas the PM emission reaches its maximum value in congested areas. For asymmetric lane-changing conditions, the lane exchange rate of vehicles and PM emissions both reach the maximum values almost simultaneously. In addition, the flow, lane-changing rate and PM emissions in both lanes are the same under the symmetrical lane change rule. Under the asymmetric lane-changing conditions, the flow, lane-changing rate and PM emissions in the lane A are higher than those in the lane B.

Comparison of PM10 emission flux of two fugitive area sources based on the real-time flux monitoring results

Due to a high concentration of particulate matter (PM10), the Korean Peninsula experienced its first poor air quality event of the year between November 19 and November 26, 2021. This study analyzes the reasons behind the occurrence of high-concentration PM10, using the real-time PM10 fugitive emission fluxes and meteorological data measured at two landfills for fly ash of coal-fired power plants located on the west coast. The real-time fugitive emission fluxes of PM10 were estimated at two different locations by a flux-gradient technique based on the eddy covariance method. The measurement results show a weak correlation between PM10 and various meteorological factors in the two places when PM10 levels are low. However, high PM10 concentrations were found to be strongly associated with the relative humidity of site A and the friction velocity of site B, respectively. High emission fluxes were observed at both sites under elevated temperature, high humidity, low wind speed, low frictional velocity, and atmospheric instability. The variation in weather patterns witnessed during periods of high PM10 concentrations in the two locations indicates that the causes of PM10 accumulation are different. The study demonstrates that the gradient-flux method's real-time measurement of fugitive emissions can explain the origin of high PM10 levels and provide essential data to efficiently regulate PM10.

Effect of ferrocene as a combustion catalyst on the premixed combustion flame characteristics of Jatropha biodiesel

Fuel additives are widely used to optimize the combustion process, reduce the harmful emissions, and improve the performance of engines. Among the metal-based additives, ferrocene is soluble in most fuels, including biodiesel. Furthermore, it is easily available and has high stability, low toxicity, and high lipophilicity. It can evenly disperse in biodiesel without causing any change in the physicochemical properties. Therefore, it can serve as an effective combustion catalyst for biodiesel. In this study, the effect of ferrocene as a combustion catalyst on the pyrolysis and combustion performance of Jatropha biodiesel is investigated. The coupled technique of thermogravimetry-Fourier transform infrared spectroscopy-mass spectrometry (TG-FTIR-MS) is used to analyze the evolution characteristics of multicomponent gaseous products generated during the pyrolysis and high-temperature oxidation of Jatropha biodiesel (JB100) and Jatropha biodiesel + ferrocene (JBF). The laminar premixed combustion flame and pollutant emissions of JB100 and JBF are examined using a variety of techniques, including OH planar laser-induced fluorescence (OH-PLIF), flue gas analysis, spectral analysis, transmission electron microscopy, etc. The results reveal that after adding ferrocene, the activation energy for the pyrolysis reaction of JB100 decreases by 4.66 kJ/mol and the complete weight loss temperature decreases by 10 ℃. Further, the addition of ferrocene reduces the endothermic heat by 0.38 mW/mg during the initial stage of the high-temperature oxidation reaction of JB100, and the amounts of final products CO2 and H2O are increased. Compared with JB100, JBF shows an enhanced OH group intensity in the combustion flame and a lower soot spectral peak. Furthermore, compared with JB100, under JBF combustion, the pollutant PM2.5 emissions decrease by 13.3 %, PM10 emissions decrease by 13.2 %, PM> 10 particulate matter emissions decrease by 19.3 %, CO emissions decrease by 6.8 %, NOx emissions increase by 21.2 %, and the size of soot particles decreases by 20.8 %.

An Assessment of the Development of a Mobile Agricultural Biogas Plant in the Context of a Cogeneration System

This article presents examples of cogeneration systems, which are standard equipment for biogas installations, based on the production of heat and electricity. It has been shown that in the case of microgeneration, ease of servicing and low installation costs are crucial. Characteristic aspects of developing concepts for mobile installations (small scale) that produce biogas, often with a simple container structure that is ready to be located in the economic infrastructure of the agricultural industry, were indicated. Recommendations for the operation of micro-biogas models are presented, which have the greatest impact on the advisability of using agricultural waste for energy purposes. A characteristic farm was selected, which has a substrate necessary for the process of methane fermentation of slurry from pig farming. The cogenerator, which constitutes a potential energy demand from the point of view of Polish agriculture in the context of renewable energy production, was analyzed. The research goal was to adapt the cogenerator to the conditions existing on a farm, which should meet the technical and technological expectations for the process of managing the produced methane with a value of 80% in agricultural biogas. The assessment of the impact of the amount of biogas on the level of CO, NO, NO2 and PM emissions was carried out at a constant engine speed for various load levels; the percentage of biogas was changed from 40 to approximately 70–80%, i.e., until significant knocking combustion was detected in the tested engines. As a result, the existing control and control system for the operation of the cogeneration unit prevents the most effective mode of operation of the research installation as a prosumer micro-installation. When the AG20P biogas unit operated in parallel with the grid with an active power of up to 11.7 kW, the electricity produced by the unit met the adopted assumptions and requirements. What is new in this article is the use of a cogeneration unit that has been adapted to its functionality, taking into account the assessment of the prospects for optimizing the cogeneration system in the context of the use of renewable energy sources as agricultural biogas. The best method was to attempt to determine the operating conditions of the cogenerator to develop the optimization of a biogas cogeneration unit producing electricity and heat in a micro-installation for the needs of an individual farm.

Reductions of multiple air pollutants from coking industry through technology improvements and their impacts on air quality and health risks in a highly industrialized region of China

The Beijing-Tianjin-Hebei (BTH) region, a highly industrialized area in China, boasts a concentration of coking plants that constitute a vital component of the steel industry. In recent years, the Chinese government has implemented measures including backward production capacity elimination (BPCE), ultra-low emission technology transformation (ULET), and deep treatment of volatile organic compounds (DTV), to promote technological progress in the coking industry and mitigate the impact of pollutant emissions. This study focuses on the emission trends, reduction effects of various measures, and the impact on air quality and human health in the regional scale. The findings reveal that in 2015, the emissions of PM, SO2, NOx and VOCs of the coking industry in BTH region were 29.15, 9.64, 26.62 and 82.99 Gg (1000 tons/year) respectively. However, by 2019, these emissions had significantly decreased by 19.95, 5.78, 18.69, and 22.53 Gg, respectively. Of these reductions, ULET contributed about 80.3 % of NOx and SO2, and 57.4 % of PM. Meanwhile, DTV and BPCE contributed 49.2 % and 50.7 % of VOCs emission reduction, respectively. Despite the improvement effect on PM2.5, SO2, and NO2 is limited, the substantial decrease in VOCs (particularly benzene) resulted in a significant reduction in the coking industry's contribution to the atmospheric benzene concentration, dropping from 15.9 % in 2015 to 11.6 % in 2019. Moreover, the lifetime cancer risk (LCR) contribution of benzene inhalation in the BTH region also decreased from 1.7 × 10−6 to 1.2 × 10−6. Looking ahead to 2025, the continued implementation of DTV will be expected to reduce VOCs emissions by 24.41Gg. This will bring the industry's contribution to the benzene concentration down to 6.8 % and the cancer risk of the population to an acceptable level (LCR < 1 × 10−6). Additionally, the deep treatment of VOCs in coking plants will significantly reduce the health risks faced by people living in the vicinity of the plants.

Towards sustainable transport: quantifying and mitigating pollutant emissions from heavy-duty diesel trucks in Northeast China.

Heavy-duty diesel trucks (HDDTs) have caused serious environmental pollution in China. Accurate estimation of their pollutant emission characteristics is essential to reduce emissions and associated environmental and public health impacts. To achieve sustainable development for transport emissions in Northeast China, we developed localized emission factors and a high-resolution emission inventory of HDDTs, based on on-board test, Guidebook and international vehicle emission (IVE) model. The results show that the total emissions of CO, NO, NO2, and PM from HDDTs in Northeast China in 2020 were 172.2 kt, 531.5 kt, 11.2 kt, and 921.4 t, respectively. In terms of spatial distribution, emissions decreased from the city center to the city fringe. Temporally, the NOx emission variation curves of different types of roads presented a "single-peak" emission characteristic, which was different from the peak of traffic flow. Three emission reduction scenarios are further developed in the paper. Scenario analysis shows that elimination of HDDTs that follow the old China III emission standard and installing tailpipe treatment devices are the most effective pollutant reduction measure. The reduction percentages for CO, NO, NO2, and PM ranged from 62.9 to 83.89%. The results of our study could inform policymakers to devise feasible strategies to reduce vehicle pollution in Northeast China.

Investigation of NOx and related secondary pollutants at Anand Vihar, one of the most polluted area of Delhi

This research investigates the influence of meteorological parameters on NOx concentrations, particularly NO2, and related secondary & primary pollutants at the Anand Vihar interstate bus terminal in Delhi. Statistical analysis of long-term data (2016–2021) examines seasonal, weekly, and daily variations in NOx and other pollutants. Temperature and relative humidity show a significant impact on NO2 levels. Seasonal patterns reveal lower concentrations during the monsoon season and higher concentrations in winter and post-monsoon periods, except for ozone. The year 2018 stands out as the most polluted for NO2. Vehicular activities directly influence pollution, evident through reduced NO2 and benzene levels during the COVID-19 lockdown. The Planetary Boundary Layer (PBL) height plays a critical role, with lower PBL heights associated with increased NO2 concentrations. Electric Vehicles (EVs) have a positive effect on reducing NO2 pollution. Comparison with a less transportation-impacted site highlights higher NO2 concentrations in areas with heavy vehicular traffic, emphasizing the need for pollution control measures and sustainable transportation. Correlation and regression analyses confirm the interdependence between PM and NO emissions, underscoring the significance of addressing vehicular emissions for effective pollution mitigation. This study provides valuable insights into the intricate relationship between meteorological parameters, vehicular emissions, and NOx concentrations.

Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model

Soil-derived dust emissions have been widely associated with health and environmental problems and should therefore be accurately and reliably estimated and assessed. Of these emissions, the inhalable PM10 and PM2.5 are difficult to estimate. Consequently, to calculate PM10 and PM2.5 emissions from soil erosion, an approach based on an artificial neural network (ANN) model which provides a multilayered, fully connected framework that relates input parameters and outcomes was proposed in this study. Owing to the difficulty in obtaining the actual emissions of soil-derived PM10 and PM2.5 over a broad area, the PM10 and PM2.5 simulated results of the ANN model were compared with the published results simulated by the widely used wind erosion prediction system (WEPS) model. The PM10 and PM2.5 emission results, based on the WEPS, agreed well with the field data, with R2 values of 0.93 and 0.97, respectively, indicating the potential for using the WEPS results as a reference for training the ANN model. The calculated r, RMSE and MAE for the results simulated by the WEPS and ANN were 0.78, 3.37 and 2.31 for PM10 and 0.79, 1.40 and 0.91 for PM2.5, respectively, throughout Southern Xinjiang. The uncertainty of the soil-derived PM10 and PM2.5 emissions at a 95% CI was (−66–106%) and (−75–108%), respectively, in 2016. The results indicated that by using parameters that affect soil erodibility, including the soil pH, soil cation exchange capacity, soil organic content, soil calcium carbonate, wind speed, precipitation and elevation as input factors, the ANN model could simulate soil-derived particle emissions in Southern Xinjiang. The results showed that when the study domain was reduced from the entire Southern Xinjiang region to its five administrative divisions, the performance of the ANN improved, producing average correlation coefficients of 0.88 and 0.87, respectively, for PM10 and PM2.5. The performances of the ANN differed by study period, with the best result obtained during the sand period (March to May) followed by the nonheating (June to October) and heating periods (November to February). Wind speed, precipitation and soil calcium carbonate were the predominant input factors affecting particle emissions from wind erosion sources. The results of this study can be used as a reference for the wind erosion prevention and soil conservation plans in Southern Xinjiang.

The Combined Effects of Hourly Multi-Pollutant on the Risk of Ambulance Emergency Calls: A Seven-Year Time Series Study.

Ambulance emergency calls (AECs) are seen as a more suitable metric for syndromic surveillance due to their heightened sensitivity in reflecting the health impacts of air pollutants. Limited evidence has emphasized the combined effect of hourly air pollutants on AECs. This study aims to investigate the combined effects of multipollutants (i.e., PM2.5, PM10, Ozone, NO2, and SO2) on all-cause and cause-specific AECs by using the quantile g-computation method. We used ambulance emergency dispatch data, air pollutant data, and meteorological data from between 1 January 2013 and 31 December 2019 in Shenzhen, China, to estimate the associations of hourly multipollutants with AECs. We followed a two-stage analytic protocol, including the distributed lag nonlinear model, to examine the predominant lag for each air pollutant, as well as the quantile g-computation model to determine the associations of air pollutant mixtures with all-cause and cause-specific AECs. A total of 3,022,164 patients were identified during the study period in Shenzhen. We found that each interquartile range increment in the concentrations of PM2.5, PM10, Ozone, NO2, and SO2 in 0-8 h, 0-8 h, 0-48 h, 0-28 h, and 0-24 h was associated with the highest risk of AECs. Each interquartile range increase in the mixture of air pollutants was significantly associated with a 1.67% (95% CI, 0.12-3.12%) increase in the risk of all-cause AECs, a 1.81% (95% CI, 0.25-3.39%) increase in the risk of vascular AECs, a 1.77% (95% CI, 0.44-3.11%) increase in reproductive AECs, and a 2.12% (95% CI, 0.56-3.71%) increase in AECs due to injuries. We found combined effects of pollutant mixtures associated with an increased risk of AECs across various causes. These findings highlight the importance of targeted policies and interventions to reduce air pollution, particularly for PM, Ozone, and NO2 emissions.