Journal: Atmospheric environment (Oxford, England : 1994)
Global aviation operations contribute to anthropogenic climate change via a complex set of processes that lead to a net surface warming. Of importance are aviation emissions of carbon dioxide (CO2), nitrogen oxides (NOx), water vapor, soot and sulfate aerosols, and increased cloudiness due to contrail formation. Aviation grew strongly over the past decades (1960-2018) in terms of activity, with revenue passenger kilometers increasing from 109 to 8269 billion km yr-1, and in terms of climate change impacts, with CO2 emissions increasing by a factor of 6.8-1034 Tg CO2 yr-1. Over the period 2013-2018, the growth rates in both terms show a marked increase. Here, we present a new comprehensive and quantitative approach for evaluating aviation climate forcing terms. Both radiative forcing (RF) and effective radiative forcing (ERF) terms and their sums are calculated for the years 2000-2018. Contrail cirrus, consisting of linear contrails and the cirrus cloudiness arising from them, yields the largest positive net (warming) ERF term followed by CO2 and NOx emissions. The formation and emission of sulfate aerosol yields a negative (cooling) term. The mean contrail cirrus ERF/RF ratio of 0.42 indicates that contrail cirrus is less effective in surface warming than other terms. For 2018 the net aviation ERF is +100.9 mW (mW) m-2 (5-95% likelihood range of (55, 145)) with major contributions from contrail cirrus (57.4 mW m-2), CO2 (34.3 mW m-2), and NOx (17.5 mW m-2). Non-CO2 terms sum to yield a net positive (warming) ERF that accounts for more than half (66%) of the aviation net ERF in 2018. Using normalization to aviation fuel use, the contribution of global aviation in 2011 was calculated to be 3.5 (4.0, 3.4) % of the net anthropogenic ERF of 2290 (1130, 3330) mW m-2. Uncertainty distributions (5%, 95%) show that non-CO2 forcing terms contribute about 8 times more than CO2 to the uncertainty in the aviation net ERF in 2018. The best estimates of the ERFs from aviation aerosol-cloud interactions for soot and sulfate remain undetermined. CO2-warming-equivalent emissions based on global warming potentials (GWP* method) indicate that aviation emissions are currently warming the climate at approximately three times the rate of that associated with aviation CO2 emissions alone. CO2 and NOx aviation emissions and cloud effects remain a continued focus of anthropogenic climate change research and policy discussions.
We estimate future wildfire activity over the western United States during the mid-21(st) century (2046-2065), based on results from 15 climate models following the A1B scenario. We develop fire prediction models by regressing meteorological variables from the current and previous years together with fire indexes onto observed regional area burned. The regressions explain 0.25-0.60 of the variance in observed annual area burned during 1980-2004, depending on the ecoregion. We also parameterize daily area burned with temperature, precipitation, and relative humidity. This approach explains ~0.5 of the variance in observed area burned over forest ecoregions but shows no predictive capability in the semi-arid regions of Nevada and California. By applying the meteorological fields from 15 climate models to our fire prediction models, we quantify the robustness of our wildfire projections at mid-century. We calculate increases of 24-124% in area burned using regressions and 63-169% with the parameterization. Our projections are most robust in the southwestern desert, where all GCMs predict significant (p<0.05) meteorological changes. For forested ecoregions, more GCMs predict significant increases in future area burned with the parameterization than with the regressions, because the latter approach is sensitive to hydrological variables that show large inter-model variability in the climate projections. The parameterization predicts that the fire season lengthens by 23 days in the warmer and drier climate at mid-century. Using a chemical transport model, we find that wildfire emissions will increase summertime surface organic carbon aerosol over the western United States by 46-70% and black carbon by 20-27% at midcentury, relative to the present day. The pollution is most enhanced during extreme episodes: above the 84(th) percentile of concentrations, OC increases by ~90% and BC by ~50%, while visibility decreases from 130 km to 100 km in 32 Federal Class 1 areas in Rocky Mountains Forest.
One of the multi-facet impacts of lockdowns during the unprecedented COVID-19 pandemic was restricted economic and transport activities. This has resulted in the reduction of air pollution concentrations observed globally. This study is aimed at examining the concentration changes in air pollutants (i.e., carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matters (PM2.5 and PM10) during the period March-April 2020. Data from both satellite observations (for NO2) and ground-based measurements (for all other pollutants) were utilized to analyze the changes when compared against the same months between 2015-2019. Globally, space borne NO2 column observations observed by satellite (OMI on Aura) were reduced by approximately 9.19% and 9.57%, in March and April 2020, respectively because of public health measures enforced to contain the coronavirus disease outbreak (COVID-19). On a regional scale and after accounting for the effects of meteorological variability, most monitoring sites in Europe, USA, China, and India showed declines in CO, NO2, SO2, PM2.5, and PM10 concentrations during the period of analysis. An increase in O3 concentrations occurred during the same period. Meanwhile, four major cities case studies i.e. in New York City (USA), Milan (Italy), Wuhan (China), and New Delhi (India) have also shown a similar reduction trends as observed on the regional scale, and an increase in ozone concentration. This study highlights that the reductions in air pollutant concentrations have overall improved global air quality likely driven in part by economic slowdowns resulting from the global pandemic.
The Iowa City Landfill in eastern Iowa, United States, experienced a fire lasting 18 days in 2012, in which a drainage layer of over 1 million shredded tires burned, generating smoke that impacted the surrounding metropolitan area of 130,000 people. This emergency required air monitoring, risk assessment, dispersion modeling, and public notification. This paper quantifies the impact of the fire on local air quality and proposes a monitoring approach and an Air Quality Index (AQI) for use in future tire fires and other urban fires. Individual fire pollutants are ranked for acute and cancer relative risks using hazard ratios, with the highest acute hazard ratios attributed to SO2, particulate matter, and aldehydes. Using a dispersion model in conjunction with the new AQI, we estimate that smoke concentrations reached unhealthy outdoor levels for sensitive groups out to distances of 3.1 km and 18 km at 24-h and 1-h average times, respectively. Modeled and measured concentrations of PM2.5 from smoke and other compounds such as VOCs and benzo[a]pyrene are presented at a range of distances and averaging times, and the corresponding cancer risks are discussed. Through reflection on the air quality response to the event, consideration of cancer and acute risks, and comparison to other tire fires, we recommend that all landfills with shredded tire liners plan for hazmat fire emergencies. A companion paper presents emission factors and detailed smoke characterization.
The coronavirus disease 2019 (COVID-19) induced a lockdown that has resulted in a sharp reduction in air and motor traffic and industrial activities. This in turn led to a reduction in air pollution around the world. It is important to quantify the extent of that reduction in order to estimate the weight of the impact of air and motor traffic and industrial activities over the total variation of air quality. An assessment of the extent of air pollution is aimed at facilitating the crafting of policies toward the reduction of pollution and the improvement in air quality. The aim of this paper is to evaluate the impact of the COVID-19 outbreak on air pollution in Israel. Particularly, we focus on Haifa and Greater Tel-Aviv (Gush-Dan), two regions with high air pollution, while examining different types of air monitoring stations. The period to which we refer to is March 8, 2020, to May 2, 2020. The results reveal two main findings: (1) During the COVID-19 lockdown, pollution emissions decreased relative to the same period in 2019. The biggest reduction was observed in NO x , which, on average, was 41%. Surprisingly, ground-level ozone (O 3) increased, and appeared to behave similarly to the ozone weekend effect. (2) The total percentage variation in pollution emission that was explained by the lockdown was at most 26%. By adding the meteorological conditions (which included measures of wind direction, wind speed, and temperature) as a factor in addition to the lockdown effect, this percent increased to 47%.
The increase of surface ozone during the Corona Virus Disease 2019 (COVID-19) lockdown in China has aroused great concern. In this study, we combine 1.5 years of measurements for ozone, volatile organic compounds (VOCs), and nitrogen oxide (NOX) at four sites to investigate the effect of COVID-19 lockdown on surface ozone in Dongguan, an industrial city in southern China. We show that the average concentrations of NOX and VOCs decreased by 70%-77% and 54%-68% during the lockdown compared to pre-lockdown, respectively. Based on the source apportionment of VOCs, the contribution of industrial solvent use reduced significantly (86%-94%) during the lockdown, and climbed back slowly along with the re-opening of the industry after lockdown. A slight increase in mean ozone concentration (3%-14%) was observed during the lockdown. The rise of ozone was the combined effect of substantial increase at night (58%-91%) and small reduction in the daytime (1%-17%). These conflicting observations in ozone response between day and night to emission change call for a more detailed approach to diagnostic ozone production response with precursor changes, rather than directly comparing absolute concentrations. We propose that the ratio of daily Ox (i.e. ozone + NO2) enhancement to solar radiation can provide a diagnostic parameter for ozone production response during the lockdown period. Smaller ratio of daily OX (ozone + NO2) enhancement to solar radiation during the lockdown were observed from the long-term measurements in Dongguan, suggesting significantly weakened photochemistry during the lockdown successfully reduces local ozone production. Our proposed approach can provide an evaluation of ozone production response to precursor changes from restrictions of social activities during COVID-19 epidemic and also other regional air quality abatement measures (e.g. public mega-events) around the globe.
The limited knowledge about the mechanism of SARS-CoV-2 transmission is a current challenge on a global scale. Among possible transmission routes, air transfer of the virus is thought to be prominent. To investigate this further, measurements were conducted at Razi hospital in Ahvaz, Iran, which was selected to treat COVID-19 severe cases in the Khuzestan province. Passive and active sampling methods were employed and compared with regard to their efficiency for collection of airborne SARS-COV-2 virus particles. Fifty one indoor air samples were collected in two areas, with distances of less than or equal to 1 m (patient room) and more than 3 m away (hallway and nurse station) from patient beds. A simulation method was used to obtain the virus load released by a regularly breathing or coughing individual including a range of microdroplet emissions. Using real-time reverse transcription polymerase chain reaction (RT-PCR), 11.76% (N=6) of all indoor air samples (N=51) collected in the COVID-19 ward tested positive for SARS-CoV-2 virus, including 4 cases in patient rooms and 2 cases in the hallway. Also, 5 of the 6 positive cases were confirmed using active sampling methods with only 1 based on passive sampling. The results support airborne transmission of SARS-CoV-2 bioaerosols in indoor air. Multivariate analysis showed that among 15 parameters studied, the highest correlations with PCR results were obtained for temperature, relative humidity, PM levels, and presence of an air cleaner.
The COVID-19 pandemic brought about national restrictions on people’s movements, in effect commencing a socially engineered transport emission reduction experiment. In New Zealand during the most restrictive alert level (Level 4), roadside concentrations of nitrogen dioxide (NO2) were reduced 48-54% compared to Business-as-usual (BAU) values. NO2 concentrations rapidly returned to near mean levels as the alert levels decreased and restrictions eased. PM10 and PM2.5 responded differently to NO2 during the different alert levels. This is due to particulates having multiple sources, many of natural origin and therefore less influenced by human activity. PM10 and PM2.5 concentrations were reduced during alert level 4 but to a lesser extent than NO2 and with more variability across regions. Particulate concentrations increased notably during alert level 2 when many airsheds reported concentrations above the BAU means. To provide robust BAU reference concentrations, simple 5-year means were calculated along with predictions from machine learning modelling that, in effect, removed the influence of meteorology on observed concentrations. The results of this study show that latter method was found to be more closely aligned to observed values for NO2 as well as PM2.5 and PM10 away from coastal regions.
This research used data mining approaches to better understand factors affecting the formation of secondary organic aerosol (SOA). Although numerous laboratory and computational studies have been completed on SOA formation, it is still challenging to determine factors that most influence SOA formation. Experimental data were based on previous work described by Offenberg et al. (2017), where volume concentrations of SOA were measured in 139 laboratory experiments involving the oxidation of single hydrocarbons under different operating conditions. Three different data mining methods were used, including nearest neighbor, decision tree, and pattern mining. Both decision tree and pattern mining approaches identified similar chemical and experimental conditions that were important to SOA formation. Among these important factors included the number of methyl groups for the SOA precursor, the number of rings for the SOA precursor, and the presence of dinitrogen pentoxide (N2O5).
In 2020, most countries around the world have observed varying degrees of public lockdown measures to mitigate the transmission of SARS-CoV-2. As an unintended consequence of reduced transportation and industrial activities, air quality has dramatically improved in many major cities around the world. In this paper, we analyze the environmental impact of the lockdown measures on P M 2.5 concentration levels in 48 core-based statistical areas (CBSA) of the United States, during the pre and post-lockdown period of January to June, 2020. We model the effect of lockdown on the P M 2.5 concentration in different CBSAs while adjusting for various meteorological factors like temperature, wind-speed, precipitation and snow. Linear mixed effects models and functional regression methods with random intercepts are employed to capture the heterogeneity of the effect across different regions. Our analysis shows there is a statistically significant reduction in levels of P M 2.5 across most of the regions during the lock-down period, although interestingly, this effect is not uniform across all the CBSAs under consideration.