Local Air Pollution Research Articles

Pollution, severe health conditions, and extreme right-wing ideology: A tale of three contemporary challenges

By exploiting the microgeography of local air pollution at the 1km-by-1 km grid-level, we link local air quality to the voting intentions of a nationally-representative sample of 27,000 UK residents. We find a causal link between air pollution and support for far-right parties: a unit increase in pollution leads to a 3% rise in the probability to support these parties. These intentions are stronger for lung disease and cancer sufferers.

Impact of single and combined local air pollution mitigation measures in an urban environment

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

The Role of Neighborhood Air Pollution in Disparate Racial and Ethnic Asthma Acute Care Use.

Rationale: The share of Black or Latinx residents in a census tract remains associated with asthma-related emergency department (ED) visit rates after controlling for socioeconomic factors. The extent to which evident disparities relate to the within-city heterogeneity of long-term air pollution exposure remains unclear. Objectives: To investigate the role of intraurban spatial variability of air pollution in asthma acute care use disparity. Methods: An administrative database was used to define census tract population-based incidence rates of asthma-related ED visits. We estimate the associations between census tract incidence rates and 1) average fine and coarse particulate matter, nitrogen dioxide (NO2), and sulfur dioxide (SO2), and 2) racial and ethnic composition using generalized linear models controlling for socioeconomic and housing covariates. We also examine for the attenuation of incidence risk ratios (IRRs) associated with race/ethnicity when controlling for air pollution exposure. Measurements and Main Results: Fine and coarse particulate matter and SO2 are all associated with census tract-level incidence rates of asthma-related ED visits, and multipollutant models show evidence of independent risk associated with coarse particulate matter and SO2. The association between census tract incidence rate and Black resident share (IRR, 1.51 [credible interval (CI), 1.48-1.54]) is attenuated by 24% when accounting for air pollution (IRR, 1.39 [CI, 1.35-1.42]), and the association with Latinx resident share (IRR, 1.11 [CI, 1.09-1.13]) is attenuated by 32% (IRR, 1.08 [CI, 1.06-1.10]). Conclusions: Neighborhood-level rates of asthma acute care use are associated with local air pollution. Controlling for air pollution attenuates associations with census tract racial/ethnic composition, suggesting that intracity variability in air pollution could contribute to neighborhood-to-neighborhood asthma morbidity disparities.

Impact Factors of Industrial Pollution and Carbon Reduction under the “Dual Carbon” Target: A Case Study of Urban Aggregation in the Pearl River Delta and Yangtze River Delta

China is facing pressure to reduce carbon emissions and control pollution. Promoting the synergy between pollution reduction and carbon reduction has become an inevitable choice to achieve the construction of a beautiful China and meet the dual carbon target. This study examines the main factors influencing industrial pollution and carbon reduction in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) urban agglomerations based on data on industrial CO2 and local air pollutants (LAP) from 2002 to 2021, using the random forest regression model. The results indicate that (1) industrial CO2 emissions have increased overall, while intensity has decreased. Additionally, both industrial LAP emissions and intensity have decreased. (2) The main factor influencing industrial CO2 and LAP emissions is the proportion of industrial value added above the scale. Additionally, the proportion of R&D internal expenditure in GDP and total trade imports and exports are the main influencing factors of industrial CO2 emissions. The industrial fume and dust removal rate mainly affects industrial LAP emissions. (3) There is a clear non-linear relationship between industrial CO2- and LAP-influencing factors and emissions, which can be attributed to the scale effect factor, the lagging effect of R&D expenditure, and the inappropriate treatment of the “three wastes” by relevant departments that is non-linear. The urban agglomerations of PRD and YRD should prioritize the reduction of carbon emissions, upgrading and transforming their industrial structures, promoting the impact of foreign trade on pollution and carbon reduction, and achieving a balance between sustainable economic development and environmental protection.

Causal effect of aviation on air pollution: An instrumental variable from faraway COVID-19 restrictions in China

The causal impacts of aviation on local air pollution are poorly understood. Leveraging variation in aviation frequency caused by COVID-19 travel restrictions that occurred hundreds of miles away between 2020 and 2022, this study identifies the short-run effect of aviation on air pollution in Hangzhou, a Chinese megacity. The results demonstrate that a one standard deviation change in aviation is associated with 12% to 21.82% changes in ambient pollution concentrations, with even more substantial pollution effects on downwind days and flights departing from Hangzhou, respectively. These estimates also remain robust to alternative specifications, satisfy external validity beyond Hangzhou and the epidemic period, and exclude pollution spillover effects. We further quantify the welfare losses from aviation pollution and find that people are willing to pay 1.76 US dollars a day in per capita household income for reducing pollution caused by each standard deviation increase in flights (i.e., 134 flights). Further analysis reveals higher economic losses resulting from pollutants at international airports. Our results underscore the need to regulate airborne contaminants from aviation in China urgently.

Carbon footprint of Nepalese healthcare system: A study of Dhulikhel Hospital

Background Though direct greenhouse gas emissions cannot be observed in health care sectors, there can exist indirect emissions contributing to global climate change. This study addresses the concept of the carbon footprint and its significance in understanding the environmental impact of human activities, with a specific emphasis on the healthcare sector through gate-to-gate (GtoG) life cycle assessment. Transportation, energy consumption, and solid waste generated by hospitals are the primary sources of carbon emissions. Methods Different standards, guidelines and parameters were used to estimate emissions from both the primary and secondary data. All steps and sub-steps involved in GtoG were accessed and analyzed within the standard ISO 14040:44 guideline. An extensive review of existing literature was carried out for the evaluation and verification of secondary data. Results The total carbon footprint of generators, electricity consumption, transportation activities, LPG cylinders, PV systems was found to be 58,780 kg-CO2-eq/yr, 519,794 kg-CO2-eq/yr, 272,375 kg-CO2-eq/yr, 44,494 kg-CO2-eq/yr, 35,283 kg-CO2-eq/yr respectively and the emissions from non-biodegradable solid waste was found to be 489,835 kg-CO2/yr. Local air pollutants such as PM10, CO, SO2, NOX, and VOCs generated by generators and transportation were also estimated. The CH4 emissions from liquid waste were 1177.344 kg CH4/BOD yr, and those from biodegradables were 3821.6954 kg CH4/yr. Conclusions Healthcare professionals and policymakers can take action to reduce the sector's carbon footprint by implementing best practices and encouraging sustainable behavior. This study can be taken as foundation for further exploration of indirect emissions from healthcare sectors not only in Nepal but also in south Asian scenario.

A Data-Driven Approach to Identify Major Air Pollutants in Shanghai Port Area and Their Contributing Factors

Air pollution is a growing concern in metropolitan areas worldwide, and Shanghai, as one of the world’s busiest ports, faces significant challenges in local air pollution control. Assessing the contribution of a specific port to air pollution is essential for effective environmental management and public health improvement, making the analysis of air pollution contributions at a selected port in Shanghai a pertinent research focus. This study aims to delve into the distribution patterns of atmospheric pollutants in port areas and their influencing factors, utilizing a data-driven approach to unveil the relationship between pollution sources and dispersion. Through a comparative analysis of pollution levels in the port’s interior, surrounding regions, and urban area concentrations, we ascertain that carbon monoxide (CO) and nitric oxide (NO) are the primary pollutants in the port, with concentrations significantly exceeding those of the surrounding areas and urban area levels. These two pollutants exhibit an hourly pattern, with lower levels during the day and higher concentrations at night. Employing a random forest model, this study quantitatively analyzes the contribution rates of different factors to pollutant concentrations. The results indicate that NO concentration is primarily influenced by operational intensity and wind speed, while CO concentration is mainly affected by meteorological factors. Further, an orthogonal experiment reveals that maintaining daily operational vehicle numbers within 5000 effectively controls NO pollution, especially at low wind speeds. Additionally, humidity and temperature exhibit similar trends in influencing NO and CO, with heightened pollution occurring within the range of 75% to 90% humidity and 6 °C to 10 °C temperature. Severe pollution accumulates under stagnant wind conditions with wind speeds below 0.2 m/s. The results help to explore the underlying mechanisms of port pollution further and use machine learning for early pollution prediction, aiding timely warnings and emission reduction strategy formulation.

Exposure to particulate matter and ozone, locations of regulatory monitors, and sociodemographic disparities in the city of Rio de Janeiro: Based on local air pollution estimates generated from machine learning models

South America is underrepresented in research on air pollution exposure disparities by sociodemographic factors, although such disparities have been observed in other parts of the world. We investigated whether exposure to and information about air pollution differs by sociodemographic factors in the city of Rio de Janeiro, the second most populous city in Brazil with dense urban areas, for 2012–2017. We developed machine learning-based models to estimate daily levels of O3, PM10, and PM2.5 using high-dimensional datasets from satellite remote sensing, atmospheric and land variables, and land use information. Cross-validations demonstrated good agreement between the estimated levels and measurements from ground-based monitoring stations: overall R2 of 76.8 %, 63.9 %, and 69.1 % for O3, PM2.5, and PM10, respectively. We conducted univariate regression analyses to investigate whether long-term exposure to O3, PM2.5, PM10 and distance to regulatory monitors differs by socioeconomic indicators, the percentages of residents who were children (0-17 years) or age 65+ years in 154 neighborhoods. We also examined the number of days exceeding the Brazilian National Air Quality Standard (BNAQS). Long-term exposures to O3 and PM2.5 were higher in more socially deprived neighborhoods. An interquartile range (IQR) increment of the social development index (SDI) was associated with a 3.6 μg/m3 (95 % confidence interval [CI]: 2.9, 4.4; p-value≤0.001) decrease in O3, and 0.3 μg/m3 (95 % CI: 0.2, 0.5; p-value = 0.010) decrease in PM2.5. An IQR increase in the percentage of residents who are children was associated with a 4.1 μg/m3 (95 % CI: 3.1, 5.0; p-value≤0.001) increase in O3, and 0.4 μg/m3 (95 % CI: 0.3, 0.6; p-value = 0.009) increase in PM2.5. An IQR increase in the percentage of residents age ≥65was associated with a 3.3 μg/m3 (95 % CI: 2.4, 4.3; p-value=<0.001) decrease in O3, and 0.3 μg/m3 (95 % CI: 0.1, 0.5; p-value = 0.058) decrease in PM2.5. There were no apparent associations for PM10. The association for daily O3 levels exceeding the BNAQS daily standard was 0.4 %p–0.8 %p different by the IQR of variables, indicating a 7–15 days difference in the six-year period. The association for daily PM2.5 levels exceeding the BNAQS daily standard showed a 0.7–1.5 %p difference by the IQR, meaning a 13–27 days difference in the period. We did not find statistically significant associations between the distance to monitors and neighborhood characteristics but some indication regarding SDI. We found that O3 levels were higher in neighborhoods situated farther from monitoring stations, suggesting that elevated levels of air pollution may not be routinely measured. Exposure disparity patterns may vary by pollutants, suggesting a complex interplay between environmental and socioeconomic factors in environmental justice.

The impact of dynamic traffic and wind conditions on green infrastructure performance to improve local air quality

Road traffic represents the dominant source of air pollution in urban street canyons. Local wind conditions greatly impacts the dispersion of these pollutants, yet street trees complicate ventilation in such settings. This case study adopts a novel modelling framework to account for dynamic traffic and wind conditions to identify the optimal street tree configuration that prevents a deterioration in air quality. Measurement data from a shallow to moderately deep street canyon (average 0.5 H/W aspect ratio and four lanes of 1-way traffic) in Dublin, Ireland was used for model calibration. The computational fluid dynamics (CFD) models were used to examine scenarios of dynamic traffic flows within each traffic lane with respect to its impact on local PM2.5 concentrations on adjacent footpaths, segmenting air quality monitoring results based on different wind conditions for model calibration. The monitoring campaign identified higher PM2.5 concentrations on the leeward (north) footpath, with average differences of 14.1 % (2.15 μg/m3) for early evening peaks. The modelling results demonstrated how street trees negatively impacted air quality on the windward footpath in parallel wind conditions regardless of leaf area density (LAD) or tree spacing, with mixed results observed on the leeward footpath in varying traffic flows and wind speeds. Perpendicular wind direction models and high wind speed exacerbated poor air quality on the windward footpath for all tree spacing models, while improving the air quality on the leeward footpath. The findings advise against planting high-LAD trees in this type of street, with a minimum of 20 m spacing for low-LAD trees to balance reducing local air pollution and ventilation capacity in the street. This study highlights the complexities of those in key decision-marking roles and demonstrates the need to adopt a transparent framework to ensure adequate modelling evidence can inform tree planting in city streets.

Ports and their influence on local air pollution and public health: A global analysis

Despite the skyrocketing growth in recent decades of environmental studies on ports and shipping, their local health impacts remain largely under-researched. This article tackles this gap in research by statistically analyzing data on global shipping flows across nearly 5000 ports in 35 OECD countries between 2001 and 2018. The different traffic types, from containers to bulk and passengers, are analyzed jointly with data on natural conditions, air pollution, socio-economic indicators, and public health. The principal results show that port regions pollute more than non-port regions on average, while health impacts vary according to the size and specialization of the port region. Three types of port regions are clearly differentiated: industrial, intermediate, and metropolitan port regions.

Impact of urbanization on fine particulate matter concentrations over central Europe

Abstract. Rural-to-urban transformation (RUT) is the process of turning a rural or natural land surface into an urban one, which brings about important modifications in the surface, causing well-known effects like the urban heat island (UHI), reduced wind speeds, and increased boundary layer heights. Moreover, with concentrated human activities, RUT introduces new emission sources which greatly perturb local and regional air pollution. Particulate matter (PM) is one of the key pollutants responsible for the deterioration of urban air quality and is still a major issue in European cities, with frequent exceedances of limit values. Here we introduce a regional chemistry–climate model (regional climate model RegCM coupled offline to chemistry transport model CAMx) study which quantifies how the process of RUT modified the PM concentrations over central Europe including the underlying controlling mechanisms that contribute to the final PM pollution. Apart from the two most studied ones, (i) urban emissions and (ii) urban canopy meteorological forcing (UCMF; i.e. the impact of modified meteorological conditions on air quality), we also analyse two less studied contributors to RUT's impact on air quality: (iii) the impact of modified dry-deposition velocities (DVs) due to urbanized land use and (iv) the impact of modified biogenic emissions due to urbanization-induced vegetation modifications and changes in meteorological conditions which affect these emissions. To calculate the magnitude of each of these RUT contributors, we perform a cascade of simulations, whereby each contributor is added one by one to the reference state, while focus is given on PM2.5 (particulate matter with diameter less then 2.5 µm). Its primary and secondary components, namely primary elemental carbon (PEC), sulfates (PSO4), nitrates (PNO3), ammonium (PNH4), and secondary organic aerosol (SOA), are analysed too. The validation using surface measurements showed a systematic negative bias for the total PM2.5, which is probably caused by underestimated organic aerosol and partly by the negative bias in sulfates and elemental carbon. For ammonium and nitrates, the underestimation is limited to the warm season, while for winter, the model tends to overestimate their concentrations. However, in each case, the annual cycle is reasonably captured. We evaluated the RUT impact on PM2.5 over a sample of 19 central European cities and found that the total impact of urbanization is about 2–3 and 1–1.5 µg m−3 in winter and summer, respectively. This is mainly driven by the impact of emissions alone causing a slightly higher impact (1.5–3.5 and 1.2–2 µg m−3 in winter and summer), while the effect of UCMF was a decrease at about 0.2–0.5 µg m−3 (in both seasons), which was mainly controlled by enhanced vertical eddy diffusion, while increases were modelled over rural areas. The transformation of rural land use into an urban one caused an increase in dry-deposition velocities by around 30 %–50 %, which alone resulted in a decrease in PM2.5 by 0.1–0.25 µg m−3 in both seasons. Finally, the impact of biogenic emission modifications due to modified land use and meteorological conditions caused a decrease in summer PM2.5 of about 0.1 µg m−3, while the winter effects were negligible. The total impact of urbanization on aerosol components is modelled to be (values indicate winter and summer averages) 0.4 and 0.3 µg m−3 for PEC, 0.05 and 0.02 µg m−3 for PSO4, 0.1 and 0.08 µg m−3 for PNO3, 0.04 and 0.03 µg m−3 for PNH4, and 0 and 0.05 µg m−3 for SOA. The main contributor of each of these components was the impact of emissions, which was usually larger than the total impact due to the fact that UCMF was counteracted with a decrease. For each aerosol component, the impact of modified DV was a clear decrease in concentration, and finally, the modifications of biogenic emissions impacted SOA predominantly, causing a summer decrease, while a very small secondary effect of secondary inorganic aerosol was modelled too (they increased). In summary, we showed that when analysing the impact of urbanization on PM pollution, apart from the impact of emissions and the urban canopy meteorological forcing, one also has to consider the effect of modified land use and its impact on dry deposition. These were shown to be important in both seasons. For the effect of modified biogenic emissions, our calculations showed that they act on PM2.5 predominantly through SOA modifications, which only turned out to be important during summer.

Can the opening of high-speed rail boost the reduction of air pollution and carbon emissions? Quasi-experimental evidence from China

This study utilizes panel data from 282 cities in China and employs the difference-in-differences method, mediating effect model, social network analysis method, and spatial econometric model to thoroughly investigate the impact of high-speed rail development on urban air pollution and carbon emissions reduction. The results of the study revealed that the introduction of high-speed railways correlated negatively with metropolitan PM2.5 and carbon emissions, suggesting a reduction in urban air pollutants and carbon emissions. The impact of high-speed rail installation on urban air pollution and carbon emissions reduction depends on various factors, such as the metropolitan area's location, size, and access to resources. Moreover, by optimizing the industrial structure and promoting technological innovation within the metropolitan region, high-speed rail installation can contribute to efforts to reduce air pollutants and carbon emissions. Over time, the influence of high-speed rail on industrial structure and technological development becomes increasingly significant. In urban centers connected to high-speed rail networks, the introduction of high-speed rail plays a significant role in fostering the reduction of urban air pollution and carbon emissions. Given the spatial correlation, the advent of high-speed rail will impact not only local air pollution and carbon reduction processes but also those of neighboring cities.

Increased Asian aerosols drive a slowdown of Atlantic Meridional Overturning Circulation

Observational evidence and climate model experiments suggest a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) since the mid-1990s. Increased greenhouse gases and the declined anthropogenic aerosols (AAs) over North America and Europe are believed to contribute to the AMOC slowdown. Asian AAs continue to increase but the associated impact has been unclear. Using ensembles of climate simulations, here we show that the radiative cooling resulting from increased Asian AAs drives an AMOC reduction. The increased AAs over Asia generate circumglobal stationary Rossby waves in the northern midlatitudes, which shift the westerly jet stream southward and weaken the subpolar North Atlantic westerlies. Consequently, reduced transport of cold air from North America hinders water mass transformation in the Labrador Sea and thus contributes to the AMOC slowdown. The link between increased Asian AAs and an AMOC slowdown is supported by different models with different configurations. Thus, reducing emissions of Asian AAs will not only lower local air pollution, but also help stabilize the AMOC.

How to perceive and map the synergy between CO2 and air pollutants: Observation, measurement, and validation from a case study of China

Cities occupy a central position in addressing climate change and promoting sustainable regional development. Synergistic control of urban gas emissions at the city level is one of the main issues typically explored. The confounding effect and the interactions between the urban indicators of population and area have been ignored in previous studies. In this study, we examined the spatial distribution characteristics and synergy between greenhouse gases (CO2) and air pollutants (SO2 and NOX) using spatial population and gas emission data. By upgrading the city clustering algorithm (CCA), we established a method for defining active areas of gas emissions (spatial element-coupled clustering, SECC) and identified active areas of gas emissions in China. In this study, we created a research framework that can simultaneously consider the effects of population and area, as well as the possible interactions between these indicators in active areas. The superlinear scaling relationship between the above three gases was revealed at the active zone level, and the existence of synergy between the emission patterns of the three gases was confirmed. Via further model application, we measured the synergistic efficiency of the three gases. It was found that for every 1% increase in SO2 and NOX in an active zone, CO2 increases by 0.86%. In this study, we explored a new perspective and approach to explain the synergy between greenhouse gases and air pollutants. This is essential to promote national competition among cities to achieve synergistic control of CO2 and local air pollutants.

Industrieschnee: An overview of some European anthropogenic snowfall events, with a case study from Bern (Switzerland)

AbstractIndustrieschnee or anthropogenic snowfall is a local winter hazard in many European cities and towns under suitable anticyclonic conditions and in the vicinity of persistent local water vapour sources and air pollution. Here, we overview the formation of Industrieschnee and describe a case study event from Bern, Switzerland, comparing the estimated mass of snow deposited with the water vapour emissions from a local incinerator. We speculate that previous European Industrieschnee events may have been considerably under‐reported, or falsely attributed to surface hoar frost (reif) or the accretion of rime (raureif).

Spatial patterns of PM2.5 air pollution in Jakarta: Insights from mobile monitoring

A mobile air quality monitoring study in Jakarta was undertaken in 2022 by the Clean Air Catalyst consortium, in partnership with Google Earth Outreach and Aclima, taking air pollution measurements using four specially equipped Google Street View cars. This study aims to map street-level PM2.5 pollution in a set of neighborhoods (polygons) throughout Jakarta to evaluate the variability caused by local emission sources and to observe the exposure to air pollution in areas with different income levels. To address these aims, we monitored the concentration five days a week, 8 am to 5 pm, from September to December in eight polygons, stratified to include high and low-income areas. The cars covered a distance of 7,750 km and at least 22 visits per location. PM2.5 concentrations were measured at 1-second intervals using a light-scattering sensor. This high-resolution data collection allowed for detailed monitoring and analysis of concentrations in the study area. The measurements showed temporal variability consistent with meteorological and activity patterns in Jakarta, with higher measured concentrations in the morning compared to the afternoon at most polygons. Median concentrations varied by 2x - &gt;5x within individual polygons, and this variability was particularly evident in the northern part of Jakarta, encompassing both high-income and low-income neighborhoods, where these areas are significantly affected by traffic and industrial activities. The results demonstrate the extent to which PM2.5 concentrations and exposures within Jakarta neighborhoods depend on proximity to local air pollution sources.

Investigation of the spatial effects on PM2.5 in relation to land use and ecological restoration in urban agglomerations

Heavy pollution of particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) poses increasing threats to the living environment worldwide. Urban agglomerations often lead to regional rather than local air pollution problems. This study explored the underlying global and local spatial driving mechanisms of PM2.5 variations of the 195 county-level administrative units in the urban agglomeration in the middle reaches of the Yangtze River, China, in 2020, using the global spatial regression and geographically weighted regression methods. Results showed that (1) at the county level, there were spatial variations of PM2.5, fluctuating from 20.1263 μg/m3 to 44.8416 μg/m3. (2) The concentrations of PM2.5 presented a positive spatial autocorrelation with a remarkable direct spatial spillover effect. (3) Forestland, grassland, elevation and ecological restoration were negatively correlated with PM2.5 concentrations, the indirect spatial spillover effect of elevation was noticeable. (4) The indirect reduction effects of ecological restoration on PM2.5 concentrations were substantial in the Wuhan urban agglomeration. (5) The reduction effect of forestland, grassland, ecological restoration and elevation on PM2.5 showed a noticeable spatial heterogeneity. In the future, it is suggested regional variability and the spatial spillover effect of air pollution be taken into account in environmental governance. Simultaneously, utilization of the mitigation effect of ecological restoration on PM2.5 is anticipated for the concerted effort in air pollution governance.

Exhaust Emission Assessment of Haulage Trucks at Onne Port, Nigeria

Haulage trucks are among the primary causes of air pollution in urban areas. The effect of air pollution caused by transportation, especially freight transportation, on public health is a major concern globally. In this study, emissions of haulage trucks operating at Onne Port, Rivers State in Nigeria were assessed to understand their contribution to local air pollution and environmental impact. Real-time measurements of air pollutants were taken using a portable Testo 350 Analyzer and a portable IGRESS Intelligent Detector from seventy (70) haulage trucks at Onne Port grouped according to production years, region of origin, and truck length, and the data obtained were compared with the World Health Organization (WHO) air quality standards. The results revealed that the trucks’ emissions exceeded WHO limits for six criteria pollutants, including NO2, SO2, CO, PM1, PM2.5, and PM10, which are associated with adverse health effects such as respiratory and cardiovascular diseases. Other notable findings included higher concentrations of NO2 at 35.48 ppm and PM2.5 at 300.73 µg/m3 from trucks produced between 2011 and 2021, while older trucks exhibited increased emissions of SO2 at 31.16 ppm, CO at 775.87 ppm, PM1 at 216.75 µg/m3, and PM10 at 341.75 µg/m3. There were no significant variations in pollutant emission concentrations observed within the four categories across different production years. Trucks manufactured in Asia consistently emitted lower pollutant concentrations compared with those from other regions, suggesting the influence of varying emission standards. Interestingly, truck length did not significantly impact emission levels. These findings underscore the urgency of addressing the air quality issues associated with haulage trucks in the region, highlighting the need for stringent emissions control measures.

Overestimated environmental benefits of short-term changes in mobility behaviour: The case of Berlin during COVID-19

The COVID-19 pandemic changed urban mobility patterns in unprecedented ways with movement decreasing, few public transport customers, and empty streets turning into pop-up bike lanes. Accordingly, a decrease in local air pollution was reported at the start of the pandemic and models suggested a lower carbon footprint of urban mobility. Here, we offer a critical discussion of the indirect environmental impacts that can be inferred from short-lived mobility behaviour. Examining Berlin, we analyse to what extent transport volume and modal split influenced direct and indirect greenhouse gas emissions throughout the pandemic (2020–2022). The analysis combines traffic counts and survey data with process-specific life cycle assessment factors. The results show that reductions in the carbon footprint of mobility during the pandemic stem largely from a short-term decline in car use, while the modal split became more carbon intensive. Emission reductions from lower use of public transport were not realised, nor a reduction of indirect emissions from vehicle production due to slowly responding upstream demand and public transport planning. This highlights the need to revise the current assumption of perfectly responding markets in environmental footprint assessment of short-term behavioural change during crises, urban experimentation, and transitions.

Evaluating emission reduction potential and co-benefits of CO2 and air pollutants from mobile sources: A case study in Shanghai, China

Mobile sources have significantly contributed to local carbon dioxide (CO2) and air pollutants (APs) emissions, but researches on their overall co-control remain limited. This study, aiming at Shanghai's overall mobile sources, conducted the prediction of emission reduction potential, co-benefits assessment and peak CO2 emissions analysis. Results revealed a reduction of 55.9% in CO2 emissions and 64.1% in APs equivalents by 2050 under the strictest scenario. Without additional mitigation, CO2 total emissions in 2050 would approach 120 Mt. Motor vehicles contribute the most to CO2 and CO emissions, while ships serve as the primary source of other APs. Motor vehicles' CO2 emissions could peak in 2033 (42.57∼47.47 Mt), with the overall mobile sources achieving peak emissions two years later (56.21∼63.55 Mt). VOCs, SO2, NOx, and CO2 exhibit relatively high synergy, and the emission reduction degree of NOx would be higher than that of CO2, while other pollutants are the opposite.