Major Source Of Air Pollution Research Articles

A Case Study of Air Quality in Kabul, Afghanistan

The air quality in Afghanistan is severely affected by various pollutant sources, the impacts of which often cause acute health problems, particularly among the old, young and those suffering from poor health. The impacts of chronic exposure to air pollutants are also likely to become apparent over time. The purpose of this air quality dissertation is to assist policy makers in the design and implementation of policies, and in the development of monitoring and management tools to restore air quality in Afghanistan. Since 2001, Kabul city’s population has grown from four hundred thousand to six million people. Estimates of various pollutant emissions indicate that vehicular traffic, windblown dust, brick kilns, residential heating during winter season, and domestic and commercial generators are the major sources of air pollution in Kabul. The estimated total annual emissions in Kabul are 17,363 tons of PM10, 16,183 tons of NOx, 2,484 tons of SO2, 97,068 tons of CO2, and 650,846 tons of CO2 .In the article “In Kabul, air pollution a bigger killer than war” that every year around 3,000 people die in Kabul city due to air pollution whereas the total mortality rate due to war across the country is 2,777 cases.

Techno-economic and Life Cycle Assessment for the Zero-Carbon Emission Process of the Production of Methanol from VOCs

Volatile organic compounds (VOCs) are one of the major sources of air pollutants, and the efficient treatment technologies for VOCs have garnered significant attention. The conventional VOCs treatment system converts VOCs into CO2 and directly releases them into air, and it is one of the biggest challenges for carbon neutrality. This paper integrates emerging water electrolysis and carbon utilization technologies with traditional VOCs thermal conversion to produce methanol in a zero-emission approach, converting harmful hydrocarbon compounds into valuable fuel, methanol, without CO2 emission. This paper conducts a comprehensive techno-economic analysis (TEA) and life cycle assessment (LCA) to evaluate their economic and environmental impacts. The research demonstrates that under current market conditions, the treatment costs for this technology range between $5.8 and $8.8 per kilogram. However, when bio-methane is utilized as a VOCs accelerant in this project, it significantly reduces the project's carbon footprint compared to traditional VOCs treatment. It provides insight into the waste-to-worth process in a zero-carbon footprint approach

The Association Between Solid Fuel Use and Lower Urinary Tract Symptoms Suggestive of Benign Prostatic Hyperplasia in Sichuan, China: Cross-Sectional Study.

Benign prostatic hyperplasia (BPH) is a global age-related disease. It has been reported that over half of the Chinese male population aged 70 years or older are experiencing BPH. Solid fuel, which is the major source of household air pollution, has been reportedly associated with several adverse events, including sex hormone disorders. Due to the certain relationship between sex hormone levels and prostate disease, the relationship between solid fuel use and lower urinary tract symptoms (LUTSs) suggestive of BPH (LUTS/BPH) deserves further exploration. This study mainly aimed to investigate the association between solid fuel use and LUTS/BPH. The data used in this study were obtained from the West China Natural Population Cohort Study. Household energy sources were assessed using questionnaires. LUTS/BPH was evaluated based on participant self-reports. We performed propensity score matching (PSM) to reduce the influence of bias and unmeasured confounders. The odds ratio (OR) and 95% CI of LUTS/BPH for the solid fuel group compared with the clean fuel group were calculated. We also conducted stratified analyses based on BMI, metabolic syndrome, waist to hip ratio, drinking status, smoking status, and age. A total of 5463 participants were included in this study, including 399 solid fuel users and 5064 clean fuel users. After PSM, the solid fuel group included 354 participants, while the clean fuel group included 701 participants. Solid fuel use was positively correlated with LUTS/BPH before and after PSM (OR 1.68, 95% CI 1.31-2.15 and OR 1.81, 95% CI 1.35-2.44, respectively). In stratified analyses, the OR of the nonsmoking group was higher than that of the smoking group (OR 2.56, 95% CI 1.56-4.20 and OR 1.47, 95% CI 0.99-2.18, respectively). Similarly, the OR of the nondrinking group was higher than that of the drinking group (OR 2.70, 95% CI 1.46-4.99 and OR 1.48, 95% CI 1.01-2.17, respectively). A positive correlation between solid fuel use and LUTS/BPH was observed. The results suggest that improving fuel structure for household cooking and other household needs can possibly help reduce the risk of LUTS/BPH.

Data fusion for enhancing urban air quality modeling using large-scale citizen science data

Rapid urbanization has led to many environmental issues, including poor air quality. With urbanization set to continue, there is an urgent need to mitigate air pollution and minimize its adverse health impacts. This study aims to advance urban air quality modelling by integrating a dispersion model output with large-scale citizen science data, collected over a 4-week period by 642 participants in Cork City, Ireland. The dispersion model enabled the identification of major sources of NO2 air pollution while also addressing gaps in regulatory monitoring efforts. Integrating the diffusion tube data with the dispersion model output, we developed a data fusion model that captured localized fluctuations in air quality, with increases of up to 22μg/m3 observed at major road intersections. The data fusion model provided a more accurate representation of NO2 concentrations, with estimates within 1.3μg/m3 of the regulatory monitoring measurement at an urban traffic location, an improvement of 11.7μg/m3 from the baseline dispersion model. This enhanced accuracy enabled a more precise assessment of the population exposure to air pollution. The data fusion model showed a higher population exposure to NO2 compared to the dispersion model, providing valuable insights that can inform environmental health policies aimed at safeguarding public health.

Estimating daily road traffic pollution in Hong Kong using CFD modelling: Validation and application

Road traffic is a major source of urban air pollution, exposing residents to harmful levels of pollutants, particularly in densely populated urban centers. In this study, Computational Fluid Dynamics (CFD) modelling is applied to investigate the impact of road traffic emissions on air pollution within a dense urban environment. The model, applied in Mong Kok, Hong Kong, incorporates high-resolution traffic activity, meteorological, and background concentration data. It demonstrates strong agreement with roadside measurements, deviating by 18.8 % for NOx, 15.5 % for CO, and 0.7 % for PM10, with potential underestimation linked to unmodeled NOx-O3 photochemistry during midday hours (12:00–17:00). Results reveal that local road traffic significantly increases background NOx levels (41 % average increase), highlighting the importance of dispersion modelling for accurate pollution assessments. Traffic-induced increases in CO and PM10 background levels are less pronounced. Two applications demonstrate the model's utility. Firstly, analysis of daily pollution distribution reveals that approximately 10 % of the studied area experiences moderate to very high pollution levels during peak hours. Secondly, an investigation into pollution sources within a leisure park identifies heavy-duty and light-duty vehicles as the primary NOx polluters. This modelling approach provides a valuable decision-making tool for policymakers and local authorities. It enables the assessment of urban design changes, strategic placement of sensitive structures, and future traffic fleet composition choices to mitigate pollution exposure. As air quality regulations tighten, this study offers a robust method for guiding impactful mitigation strategies.

Unlocking the potential of electric and hybrid tractors via sensitivity and techno-economic analysis

The majority of agricultural vehicles in use today still rely on diesel-based propulsion, a major source of air pollution. Electrification is seen as a potential solution for decarbonizing these off-road vehicles but is hampered by higher upfront costs in energy storage and charging infrastructure. To better quantify these barriers, this paper proposes a techno-economic tool that can assist farmers in evaluating the total costs of ownership of electric and hybrid tractors. A pragmatic simulation model of the tractor is developed to predict the annual energy/fuel consumption and NOx emissions, while an economic model estimates the total acquisition, operation, and maintenance costs. For managing the energy in hybrid tractors, a new power split strategy based on model predictive control is developed, allowing the designer to balance energy efficiency and NOx emissions, while taking into account operational constraints of the electric powertrain. Additionally, we propose novel decision maps that allow farmers to quickly identify operating regions (in term of average load and yearly working time) where the deployment of electric/hybrid tractors is economically viable. To account for variability in the tractor’s operational conditions, we conduct both a deterministic sensitivity analysis with multi-parameter variation and a stochastic analysis of the total cost of ownership. The tool is validated with different mission profiles based on data from a California farm. The results show that, compared to diesel powertrains, electric tractors are more cost-effective for light-duty farming activities (engine loads less than 20%). On the other hand, hybrid powertrains are more economical for medium-duty tasks, where engine loads range from 20% to 60%.

Unveiling urban air quality dynamics during COVID-19: a Sentinel-5P TROPOMI hotspot analysis

In India, the spatial coverage of air pollution data is not homogeneous due to the regionally restricted number of monitoring stations. In a such situation, utilising satellite data might greatly influence choices aimed at enhancing the environment. It is essential to estimate significant air contaminants, comprehend their health impacts, and anticipate air quality to safeguard public health from dangerous pollutants. The current study intends to investigate the spatial and temporal heterogeneity of important air pollutants, such as sulphur dioxide, nitrogen dioxide, carbon monoxide, and ozone, utilising Sentinel-5P TROPOMI satellite images. A comprehensive spatiotemporal analysis of air quality was conducted for the entire country with a special focus on five metro cities from 2019 to 2022, encompassing the pre-COVID-19, during-COVID-19, and current scenarios. Seasonal research revealed that air pollutant concentrations are highest in the winter, followed by the summer and monsoon, with the exception of ozone. Ozone had the greatest concentrations throughout the summer season. The analysis has revealed that NO2 hotspots are predominantly located in megacities, while SO2 hotspots are associated with industrial clusters. Delhi exhibits high levels of NO2 pollution, while Kolkata is highly affected by SO2 pollution compared to other major cities. Notably, there was an 11% increase in SO2 concentrations in Kolkata and a 20% increase in NO2 concentrations in Delhi from 2019 to 2022. The COVID-19 lockdown saw significant drops in NO2 concentrations in 2020; specifically, − 20% in Mumbai, − 18% in Delhi, − 14% in Kolkata, − 12% in Chennai, and − 15% in Hyderabad. This study provides valuable insights into the seasonal, monthly, and yearly behaviour of pollutants and offers a novel approach for hotspot analysis, aiding in the identification of major air pollution sources. The results offer valuable insights for developing effective strategies to tackle air pollution, safeguard public health, and improve the overall environmental quality in India. The study underscores the importance of satellite data analysis and presents a comprehensive assessment of the impact of the shutdown on air quality, laying the groundwork for evidence-based decision-making and long-term pollution mitigation efforts.

Human sperm mitochondrial DNA copy numbers and deletion rates: Comparing persons living in two urban industrial agglomerations differing in sources of air pollution

Persons living in industrial environments are exposed to levels of air pollution that can affect their health and fertility. The Czech capital city, Prague, and the Ostrava industrial agglomeration differ in their major sources of air pollution. In Prague, heavy traffic produces high levels of nitrogen oxides throughout the year. In the Ostrava region, an iron industry and local heating are sources of particulate matter (PM) and benzo[a]pyrene (B[a]P), especially in the winter. We evaluated the effects of air pollution on human sperm mitochondrial DNA (mtDNA). Using real-time PCR, we analysed sperm mtDNA copy number and deletion rate in Prague city policemen in two seasons (spring and autumn) and compared the results with those from Ostrava. In Prague, the sperm mtDNA deletion rate was significantly higher in autumn than in spring, which is the opposite of the results from Ostrava. The sperm mtDNA copy number did not show any seasonal differences in either of the cities; it was correlated negatively with sperm concentration, motility, and viability, and with sperm chromatin integrity (assessed with the Sperm Chromatin Structure Assay). The comparison between the two cities showed that the sperm mtDNA deletion rate in spring and the sperm mtDNA copy number in autumn were significantly lower in Prague vs. Ostrava. Our study supports the hypothesis that sperm mtDNA deletion rate is affected by the composition of air pollution. Sperm mtDNA abundance is closely associated with chromatin damage and standard semen characteristics.

A New Air-Assisted Flare Tip Design for Managing Gas Flare Emissions (CFD Analysis)

Recently, flares have been considered as a major source of air pollution from the petroleum refining industry. The United Nations has instigated an international effort related to the management of flare emissions to reduce the global warming impact related to flaring. Eliminating or removing the need for gas flares is difficult because these devices are generally used as safety devices to allow the combustion of flammable gases in a controlled fashion which supports safe operation. However, reducing flaring is generally possible using well-designed, efficiently operated flare equipment. In general, flare performance can be enhanced following the API-521 methodology and using assist-media including air and steam to achieve smokeless operation. This present work will discuss flare emissions in the petroleum refining industry and a method to manage flare emissions. Moreover, this work will discuss flare combustion efficiency (CE) and destruction and removal efficiency (DRE) in terms of efficient flare operation. This work uses actual operating flare data, published previously, which will be used in this work together with the CFD Code C3d. This code, developed at the USDOE Sandia National Laboratory, is based on a standard LES methodology to conduct transient flare analysis and is used to simulate flare operation to estimate flame shape and emissions produced. In this work, a new air-assisted flare tip design which uses the Coanda effect to improve flare operation was analyzed. This new flare design reduces the emission rate and demonstrates the design’s effectiveness. The analysis considers a flare 39″ high and 6″ diameter in the center of a 4m x 4m x 4m domain. Boundary conditions assume no cross wind and an ambient temperature of 300 K. The initial condition is a hydrostatic pressure profile across the computational domain. In the air-assist simulation, stoichiometric ratio will be a variable, and therefore, more than one case was considered.

ESTIMATION OF NITROGEN OXIDE (NOX) EMISSIONS FROM MOTOR VEHICLES BASED ON FUEL CONSUMPTION IN KUALA LUMPUR METROPOLITAN CITY, MALAYSIA

One of the major sources of urban air pollution in Kuala Lumpur is attributed to more than 17 million units of motor vehicles that have an impact on human health. This study focused on nitrogen oxide (NOx) emissions from four classes of motor vehicles such as private cars, motorcycles, and goods vehicle from 2010 to 2014 using fuel consumption analysis. The study revealed that private cars were responsible for the majority of NOx emissions, with 3,854 kg in 2010 increasing to 5,726 kg in 2014. During the same period, motorcycles emitted 1,200 kg in 2010 and 1,750 kg in 2014, while goods vehicles emitted 199 kg in 2010 and 219 kg in 2014.The results of this study are important to policymakers and stakeholders. In particular, for the planning of various strategies to reduce and control the impact of air pollution from motor vehicles, especially on human health, in Kuala Lumpur.

Effect of gasoline prices on urban air quality: Evidence from China new vehicle registrations

The emissions from motor vehicle are increasingly becoming a major source of urban air pollution in China. This study examines the impact of fuel price on expected new vehicle prices based on a hedonic valuation model. Utilizing monthly panel data from Chinese cities and employing panel ordinary least squares regression and mediation effect models, this paper finds the effects of fuel price fluctuations on new vehicle registrations and air pollution. Empirical findings indicate that rising gasoline prices lead to an improvement in urban air quality by reducing the number of new vehicle registrations. The study categorizes vehicle engine displacement into five levels, revealing that higher gasoline prices prompt residents to reduce purchases of medium-displacement vehicles and shift to small-displacement vehicles, while the impact on the registration of larger-displacement vehicles is less pronounced. The purchase tax exemption for new small-displacement vehicles has a moderating effect. Considering China's uneven economic development, the influence of gasoline prices on new vehicle registrations gradually diminishes as regional residents' incomes rise. Gasoline prices are used by regulators to guide the restructuring of vehicle consumption, thereby helping to mitigate urban environmental problems.

Distribution assessment and source apportionment of particulate bound-PAHs in indoor air of south Asian precinct using IDW and PMF receptor model: A comprehensivestudy

PAHs have been recognised as a major menace to living-beings as well as environment. Several researchers have extensively claimed regarding death-defying nature of PAHs and its derivatives. However, these studies have only considered the ambient air which is a composition of automobile exhausts, industrial emissions etc. as major source of harmful air pollutants. Indoor air quality (IAQ) is an overlooked area since, although many researchers in recent times have been working on the chemistry and composition of IAQ, yet, source determination and nature of pollutants is still a comprehensive area to be explored. With the above stated objective, the present study emphases on 16 USEPA specified PAHs which are allied with particulate matter. Both PM as well as PAHs are some very common and treacherous chemical contaminant accountable for more than a million death globally. PAHs are organic compound which are either attached to PM of various sizes or can exist in gaseous form. Current work precises the concentration of PAHs associated with fine PM i.e., PM2.5 in indoor environment of south Asian precinct, further, using receptor modelling technique for determination indoor sources responsible for the emanation of specific PAHs. The toxicity equivalent quotient i.e., TEQ evaluated in the study demonstrations that the highest toxicity among all PAHs is exhibited by BaP followed by InP, BKF, BbF. Seasonal variations in the concentration of PAHs and their respective sources were also established using PMF models, which depicted the domination of 3-ring PAHs in winter with 42% contribution in outdoors, whereas, four-ring PAHs dominion in indoors. Similarly, in summer two-ring accounted for 35% in outdoors, and three-ring PAHs contributed highest with 26.8% in indoors. In monsoon PAHs with two-ring contributed highest with 45.2% in outdoors, whereas, 2-ring PAHs contributed 38.3% in indoors. Also, IDW mapping and molecular diagnostic ratio were assessed for an intense study on distribution of PAHs in the locality and the source apportionment purpose respectively. To the best of our knowledge, the study is first of its kind in this part of the world where, majority of the countries are either developing or under-developed and hence at greater risk to the noxious effects which are often overlooked. The study will provide a clear picture regarding the indoor sources of the PAHs and further help the further professionals to build a credible and pragmatic mitigation technique accordingly.

Measurement report: Combined use of MAX-DOAS and AERONET ground-based measurements in Montevideo, Uruguay, for the detection of distant biomass burning

Abstract. Biomass burning releases large amounts of aerosols and chemical species into the atmosphere, representing a major source of air pollutants. Emissions and by-products can be transported over long distances, presenting challenges in quantification. This is mainly done using satellites, which offer global coverage and data acquisition for places that are difficult to access. In this study, ground-based observations are used to assess the abundance of trace gases and aerosols. On 24 November 2020, a significant increase in formaldehyde was observed with a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument located in Montevideo (Uruguay), and its vertical column densities reached values of 2.4×1016 molec. cm−2, more than twice the values observed during the previous days. This was accompanied by an increase in the aerosol levels measured by an AErosol RObotic NETwork (AERONET) photometer located at the same site. The aerosol optical depth (AOD) at 440 nm reached values close to 1, an order of magnitude larger than typical values in Montevideo. Our findings indicate that the increase was associated with the passage of a plume originating from distant biomass burning. This conclusion is supported by TROPOspheric Monitoring Instrument (TROPOMI) satellite observations as well as HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) simulations. The profiles of the gases and aerosols retrieved from the MAX-DOAS observations are consistent with the HYSPLIT analysis, showing the passage of a plume over Montevideo on 24 November located at a height of ∼ 1.5 km. This corroborates the finding that biomass burning events occurring about 800 km north of Montevideo can affect the local atmosphere through long-distance emissions transport. This study underscores the potential of ground-based atmospheric monitoring as a tool for detection of such events. Furthermore, it demonstrates greater sensitivity compared to satellite when it comes to detection of relatively small amounts of carbonyls like glyoxal and formaldehyde.

Short-term associations of PM10 attributed to biomass burning with respiratory and cardiovascular hospital admissions in Peninsular Malaysia.

Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events. We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex. We analyzed 210960 respiratory and 178952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions. Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.

Diesel Particulate Matter Permeation into Normal Human Skin and Intervention Using a Topical Ceramide Formulation

Introduction: Diesel particulate matter (DPM) emitted from diesel engines is a major source of air pollutants. DPM is composed of elemental carbon, which adsorbs organic compounds including toxic polycyclic aromatic hydrocarbons (PAHs). The skin, as well as airways, is directly exposed to DPM, and association of atopic dermatitis, psoriasis flares, and premature skin aging with air pollutant levels has been documented. In skin, the permeation of DPM and DPM-adsorbed compounds is primarily blocked by the epidermal permeability barrier deployed in the stratum corneum. Depending upon the integrity of this barrier, certain amounts of DPM and DPM-adsorbed compounds can permeate into the skin. However, this permeation into human skin has not been completely elucidated. Methods: We assessed the permeation of PAHs (adsorbed to DPM) into skin using ex vivo normal (barrier-competent) organ-cultured human skin after application of DPM. Two major PAHs, 2-methylnaphthalene and triphenylene, and a carcinogenic PAH, benzo(a)pyrene, all found in DPM, were measured in the epidermis and dermis using liquid chromatography electrospray ionization tandem mass spectrometry. In addition, we investigated whether a topical formulation can attenuate the permeation of DPM into skin. Results: 2-Methylnaphthalene, triphenylene, and benzo(a)pyrene were recovered from the epidermis. Although these PAHs were also detected in the dermis after DPM application, these PAH levels were significantly lower than those found in the epidermis. We also demonstrated that a topical formulation that has the ability to form more uniform membrane structures can significantly suppress the permeation of PAHs adsorbed to DPM into the skin. Conclusion: Toxic compounds adsorbed by DPM can permeate even barrier-competent skin. Hence, barrier-compromised skin, such as in atopic dermatitis, psoriasis, and xerosis, is even more vulnerable to air pollutants. A properly formulated topical mixture that forms certain membrane structures on the skin surface can effectively prevent permeation of exogenous substances, including DPM, into skin.

Environmental and Health Impact of Heavy Metal Accumulation in (Hair - Nails) of Scavenger Workers at Some Landfill Sites in Baghdad City-Iraq

Background: Heavy metals are considered one of the most dangerous environmental pollutants due to their high toxicity, even at low concentrations, and their accumulation in various body tissues. Landfills contain various wastes rich in heavy metals, such as batteries, paints, and household and hospital waste, making them a major source of air, soil, and groundwater pollution. Objective: To analyze the level of accumulation of heavy metals in hair and nail samples of waste collectors. Material and method: Five main landfill sites in the city of Baghdad were chosen to collect hair and nail samples from waste collectors of both sexes for the winter and summer seasons to analyze the levels of metal concentrations (lead, cadmium, nickel, zinc, and copper). And the use of atomic absorption spectrometry (AAS). Results: Higher concentrations of lead, copper, and nickel were found in nail samples during the summer compared to the winter, indicating an increased risk of exposure to them. While zinc accumulation was much greater in winter samples. Conclusions The results highlight the health risks faced by landfill workers. A need to develop tailored strategies to control exposure to these emissions based on weather conditions and priority metals of concern identified through regular biological monitoring.

Internalization of External Cost in the Thermal Power Generation on Social Welfare Maximization

For decades, Kenya has incorporated thermal power technology into its grid to generate electrical energy using fossil fuels such as petroleum, natural gas, and coal. The burning of fossil fuels has become a major source of air pollutants and is associated with several undesirable side effects on the environment and human health. However, the impact of pollutants on environmental sustainability and public welfare has yet to be evaluated. Therefore, the purpose of this study is to evaluate the external cost of electricity generated by thermal power plants in Kenya. Both survey data and secondary data were used. The analysis was conducted using externality valuation and welfare maximization approaches, and the research hypotheses were tested using a negative binomial regression model. The annual external cost ($/2022) was determined to be $ 1,333,904,970.76, with the following distribution: environmental at $ 993,488,336.26, Public health at $ 86,760,038.01, and socio-economic at $ 253,656,596.49. Equally, the thermal power generation marginal social cost ($/2022) was determined to be 1.22 $cents/kWh with the following distribution: Marginal Private Cost (MPC) at 0.01 $cents/kWh and Marginal External Cost (MEC) at 1.21 $cents/kWh. The established marginal social cost (MSC) (i.e. Σ MPC+MEC) was 1.22 ($cents/kWh). Thus, MSC is significantly greater than the established social marginal benefit (SMB) of 0.089 ($ cents/kWh); hence, we conclude that the burden of social welfare loss is highly significant, making thermal power a non-sustainable and economic energy source.

Exploring the relationships between 3D urban landscape patterns and PM2.5 pollution using the multiscale geographic weighted regression model

Fine particulate matter (PM2.5) is a major source of air pollution and exerts serious impacts on human health. The 3D urban landscape patterns can significantly affect the diffusion and emissions of PM2.5. However, studies on the relationships between 3D urban landscape patterns and PM2.5 pollution across different seasons remain understudied. With the ground-level air pollutants estimated by the remote sensing and fine-scale building information, this study applied the multiscale geographically weighted regression model to explore such relationships. Wuhan, the largest metropolis in Central China, was selected as the study area for the application of our methodology. The results showed that the direction, degree, and scale of the effect of 3D urban landscape patterns on PM2.5 pollution varied across seasons. For building height, the standard deviation of building height had a significant positive correlation with PM2.5 all year round. For building density, the building count density showed a significant positive correlation with PM2.5 in general, with the bandwidth in winter and autumn smaller than in spring and summer. The building plan area fraction exerted both positive and negative influences on PM2.5, dependent on season and location. The bandwidth of it gradually increased from spring to winter, with the effect changing from local to regional scale. For building volume, the floor area ratio showed a significant negative correlation with PM2.5 in winter and autumn, and a localized effect was found, especially in winter. The findings of this study provide practical implications for urban planning and policy making to mitigate PM2.5 pollution in the rapidly urbanizing regions.

A Flexible Cross-Efficiency Model with Partial Preference for Efficiency Evaluation of Clean Transportation Energy

The rapid development of the transportation industry benefits from the consumption of energy, but the excessive dependence on petroleum fuels makes it a major source of air pollution. In order to achieve green and high-quality development of the transportation industry, many countries are committed to scientifically evaluating the utilization efficiency of clean energy, which has attracted wide attention from the whole society. Significantly, without considering the diversity and complexity of pollutants, indicators used in previous studies were unable to cover all pollutants when establishing the evaluation index system. Meanwhile, as an efficient tool, data envelopment analysis (DEA) is extensively used when it comes to efficiency evaluation. However, the absolute preference of existing benevolent and aggressive cross-efficiency models limits its application scenarios. To address the challenges above, an improved flexible cross-efficiency DEA model is proposed considering both same and different benevolence coefficients of decision-making units (DMUs) on the basis of pointing out the inadequacy of the previous model. The concepts of consensus coefficient and group preference are introduced in the aggregation of cross-efficiency. Besides, based on the theory of undesirable output, the consumption of nonclean energy is taken into account as the input indicator to characterize the degree of pollution. The results show that the obtained cross-efficiency value and efficiency ranking of clean transportation energy change sensitively under various benevolent coefficients. There is an important practical significance to consider the independent preference information of DMUs for the evaluation and ranking of cross-efficiency.

Assessing total cost of driving competitiveness of zero-emission trucks

Medium- and heavy-duty vehicles are 21% of US transportation greenhouse gas (GHG) emissions and a major source of air pollution. We explore how the total cost of driving (TCD) of zero-emission vehicles (ZEVs), including battery electric vehicles and hydrogen fuel cell electric vehicles (EVs and FCEVs), could evolve under alternative scenarios. With continued improvements in vehicles and fuels, ZEVs can rapidly become viable, potentially reaching TCD parity or better compared to diesel vehicles by 2035 for all market segments. For heavy long-haul trucks, EVs become competitive on a TCD basis at charging costs below $0.18/kWh, while FCEVs become competitive on a TCD basis at hydrogen costs below $5/kg. A full transition to ZEV sales by 2035 results in 65% emissions reductions by 2050 compared to 2019 without supportive policies. Incentives such as the Inflation Reduction Act vehicle purchase credits further accelerate ZEV TCD competitiveness with major adoption opportunities over the next five years.