Where, When, and How Much Should We Pay for Wind Erosion Prevention Services of the Largest Chinese Grassland Reserve?

The large-scale and cross-regional payment for ecosystem services (PES) contributes positively to ecology-economy balance and thus helps prevent environmental challenges such as "sand storm". However, existing PES programs often overlook the connection between service-providing areas (SPAs) and service-benefiting areas (SBAs). Here, we developed an interregional PES framework based on the theory of ecosystem services flow and applied it to the largest Chinese grassland nature reserve, Xilingol Prairie, to quantitatively identify SPAs, SBAs, and flow paths of the ecosystem wind erosion prevention service (WEPS). We showed that, from 2000 to 2020, the grassland ecosystem of Xilingol Prairie had brought an annual WEPS benefit of 1.21 × 108 t/a and economic value of 12.44 × 108 CNY/a, accounting for approximately 107.71% of the GDP in the same area and year and with a slightly increasing trend in most areas. We reveal obvious seasonal (over half in the spring) and interannual variations in the benefit and that Inner Mongolia, Hebei, and Northeast China are the most important beneficiaries of WEPS, rather than Beijing and Tianjin as traditionally thought. Our results warn that the WEPS supply capacity will not last long and call for finer spatial (e.g., among cities) and temporal (e.g., focus on the spring) resolution for PES policy design.

Aerosol-PM2.5 Dynamics: In-situ and satellite observations under the influence of regional crop residue burning in post-monsoon over Delhi-NCR, India.

The increasing air pollution in the urban atmosphere is adversely impacts the environment, climate and human health. The alarming degradation of air quality, atmospheric conditions, economy and human life due to air pollution needs significant in-depth studies to ascertain causes, contributions and impacts for developing and implementing an effective policy to combat these issues. This work lies in its multifaceted approach towards comprehensive understanding and mitigating severe pollution episodes in Delhi and its surrounding areas. We investigated the aerosol dynamics in the post-monsoon season (PMS) from 2019 to 2022 under the influence of both crop residue burning and meteorological conditions. The study involves a broad spectrum of factors, including PM2.5 concentrations, active fire events, and meteorological parameters, shedding light on previously unexplored studies. The average AOD550 (0.79) and PM2.5 concentration (140.12 µg/m³) were the highest in 2019. PM2.5 was higher from mid-October to mid-November each year, exceeding the WHO guideline of 15 µg/m³ (24 h) by 27-34 times, signifying a public health emergency. A moderate to strong correlation between PM2.5 and AOD was found (r = 0.65) in 2021. The hotspot region accounts for almost 50% (2019), 47.51% (2020), 57.91% (2021) and 36.61% (2022) of the total fire events. A statistically significant negative non-linear correlation (r) was observed between wind speed (WS) and both AOD and PM2.5 concentration, influencing air quality over the region. HYSPLIT model and Windrose result show the movement of air masses predominated from the North and North-West direction during PMS. This study suggest to promotes strategies such as alternative waste management, encouraging modern agricultural practices in hot-spot regions, and enforcing strict emission norms for industries and vehicles to reducing air pollution and its detrimental effects on public health in the region and also highlights the need for future possibilities of research to attract the global attention.

Comprehensive analysis of air pollution and the influence of meteorological factors: a case study of adiyaman province.

Adiyaman, a city recently affected by an earthquake, is facing significant air pollution challenges due to both anthropogenic activities and natural events. The sources of air pollution have been investigated using meteorological variables. Elevated southerly winds, especially prominent in spring and autumn, significantly contribute to dust transport, leading to a decline in local air quality as detected by the HYSPLIT model. Furthermore, using Suomi-NPP Thermal Anomaly satellite product, it is detected and analyzed for crop burning activities. Agricultural practices, including stubble burning, contribute to the exacerbation of PM10 pollution during the summer months, particularly when coupled with winds from all directions except the north. In fall and winter months, heating is identified as the primary cause of pollution. The city center located north of the station is the dominant source of pollution throughout all seasons. The study established the connection between air pollutants and meteorological variables. Furthermore, the Spearman correlation coefficients reveal associations between PM10 and SO2, indicating moderate positive correlations under pressure conditions (r = 0.35, 0.52). Conversely, a negative correlation is observed with windspeed (r = -0.35, -0.50), and temperature also exhibits a negative correlation (r = -0.39, -0.54). During atmospheric conditions with high pressure, PM10 and SO2 concentrations are respectively 41.2% and 117.2% higher. Furthermore, pollutant concentration levels are 29.2% and 53.3% higher on days with low winds. Last, practical strategies for mitigating air pollution have been thoroughly discussed and proposed. It is imperative that decision-makers engaged in city planning and renovation give careful consideration to the profound impact of air pollution on both public health and the environment, particularly in the aftermath of a recent major earthquake.

Ecological restoration can enhance the radiation benefit of sand fixation service: A simulated evidence of Xilingol League, China.

Large-scale ecological restoration programs have been initiated globally with the aim of combating desertification and improving ecosystem services, especially for sand fixation service (SF) in arid and semi-arid regions. However, the effectiveness of ecological restoration in the radiation benefit of SF, such as improving air quality, remains not well known. In this study, we selected Xilingol as the study area, investigated the dynamics of SF, and quantified the radiation benefit of SF in downwind areas by employing PM10 concentration as the proxy. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was applied to assess the response of radiation benefit to ecological restoration by designing land use scenarios. Results showed that the SF in Xilingol increased with fluctuation at an average rate of 0.27%/year from 2000 to 2018. Under the effect of ecological restoration, the radiation benefit in the downwind regions was substantially improved, as manifested by a 104.22 µg/m3 reduction in PM10 concentration. The changes in radiation benefit varied greatly across space, and northern and southern Xilingol were hot spots for increased radiation benefit. Based on regional disparity in benefit level, this work could provide a reference to make differentiated cross-regional ecological compensation schemes at the national level.

Agricultural abandoned lands as emission sources of dust containing metals and pesticides in the Sonora-Arizona Desert.

This investigation examines the transport of metal- and pesticide-polluted dust emitted by one of the most relevant agricultural areas of Northwestern Mexico. In the contaminated area, an excessive water extraction of the aquifer and seawater intrusion caused the abandonment of fields, which are pollutant-loaded dust emitters. We used air mass forward trajectories (HYSPLIT) model to obtain particle trajectories in the wind and the use of banned pesticides as geochemical tracers for dust transported by wind. Fifty dust samples from 10 agriculture fields and 26 roof dust of a city close to the agricultural area were analyzed for their contents of zirconium, lead, arsenic, zinc, copper, iron, manganese, vanadium, and titanium, by portable X-ray fluorescence. Nine pesticides were analyzed in the roof dust and agricultural soil samples by gas chromatography. Results show that the distribution of metals was significantly different between active and abandoned fields. Arsenic-lead-copper was mainly concentrated in abandoned fields, while zinc-iron-manganese-titanium was dominant in active fields. Two potential sources of metal contamination were found by principal component analysis (PCA): (I) a mixture of traffic and agricultural sources and (II) a group related to agricultural activities. The occurrence of banned pesticides in dust deposited on roofs collected at nearby cities confirms the atmospheric transport from the agricultural area. The HYSPLIT results indicated that the dust emitted from agricultural fields can reach up to the neighboring states of Sonora, Mexico, and the USA. The impacts that these emissions can have on human health should be studied in future research.

An investigation of the effects of sand and dust storms in the North East Sahara Desert on Turkish airports and PM10 values: 7 and 8 April, 2013 events.

Between April 7 and April 10, 2013, a cyclone with a value of 995 hPa that developed in the central Mediterranean transported dust from the Sahara Desert towards Turkey. At 13 airports in Turkey, dust haze and widespread dust were seen during different occasions in this period and caused the observation of so-called "Blowing dust events." This cyclone blew dust towards the Cappadocia airport, and the prevailing visibility decreased to 3800 m, making it the lowest value measured during the transition of this cyclone. In this study, Aviation Routine Weather Report (Metar) and Aviation Selected Special Weather Report (Speci) observations of airports in North Africa and Turkey were evaluated for the period between April 3 and April 11, 2013. With this cyclone the prevailing visibility at Benina Airport in Libya decreased to 50 m on April 6, 2013. This study aims to evaluate long-distance dust transport's effects on meteorological visibility at airports in Turkey and examine the episodic changes of PM10 values measured by air quality monitoring stations. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model outputs were used to determine the trajectories of long-distance dust particles. Powder red, green, and blue (RGB) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images, Cloud-Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) images, the Barcelona Supercomputing Center-Dust Regional Atmosphere Model (BSC-DREAM8b) outputs, and Global Forecast System (GFS) synoptic maps were used for analysis. In addition, PM10 values obtained from air quality monitoring stations were examined. According to the data obtained from the CALIPSO images, the dust concentration on the Eastern Mediterranean reaches up to 5 km. The episodic values obtained from certain air quality measurement stations are Adana 701, Gaziantep 629, Karaman 900, Nevsehir 1343, and Yozgat 782 µg/m3 on an hourly average.

An urban air quality assessment based on a meteorological perspective.

An integrated approach to understanding all measured pollutants with multi-discipline in different time scales and understanding the mechanisms hidden under low air quality (AQ) conditions is essential for tackling potential air pollution issues. In this study, the air pollution of Sivas province was analyzed with meteorological and PM2.5 data over six years to assess the city's AQ in terms of PM2.5 pollution and analyze the effect of meteorological factors on it. It was found that the winter period (January-February-November-December) of every year except 2019-which has missing data-is the period with the highest air pollution in the province. In addition, the days exceeding the daily PM2.5 limit values in 2016, 2017, 2020, and 2021 were also seen in the spring and summer months, which inclined the study to focus on additional pollutant sources such as long-range dust transport and road vehicles. The year 2017 has the highest values and was analyzed in detail. Pollution periods with the most increased episodes in 2018 were analyzed with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Dust Regional Atmospheric Model (DREAM) models. As a result of the study, the average PM2.5 values in 2017 were 31.66 ± 19.2 µg/m3 and a correlation of -0.49 between temperature and PM2.5. As a result of model outputs, it was found that the inversion is intensely observed in the province, which is associated with an increase of PM2.5 during the episodes. Dust transport from northwestern Iraq and northeastern Syria is observed, especially on days with daily average PM2.5 values above 100 µg/m3. Additionally, planetary boundary layer (PBL) data analysis with PM pollution revealed a significant negative correlation (r = -0.61). Air pollutants, particularly PM2.5, were found to be higher during lower PBL levels.

Changes of air pollutants and simulation of a heavy pollution process during COVID-19 in Shenyang.

During COVID-19, Shenyang implemented strict household isolation measures, resulting in a sharp reduction in anthropogenic emission sources, providing an opportunity to explore the impact of human activities on air pollution. The period from January to April of 2020 was divided into normal period, blockade period and resumption period. Combined with meteorological and pollutant data, mathematical statistics and spatial analysis methods were used to compare with the same period of 2015-2019. The results showed that PM2.5, PM10, NO2 and O3 increased by 32.6%, 13.2%, 4.65% and 22.7% in the normal period, among which the western area changed significantly. During the blockade period, the concentration of pollutants decreased by 35.79%, 35.87%, 32.45% and -4.84%, of which the central area changed significantly. During the resumption period, the concentration of pollutants increased by 21.8%, 8.7%, 5.7% and -6.3%, and the area with the largest change was located in the western. During the blockade period, a heavy pollution occurred with PM2.5 as the main pollutant. The WRF-Chem model and the HYSPLIT model were used to reproduce the pollution occurrence process. The result showed that winds circulated as zonal winds during the pollution process at high altitudes. These winds were controlled by straight westerly and weak northwesterly airflows in front of the high pressure, and the ground was located behind the warm low pressure. Weather conditions were relatively stable. Thus, high temperatures (average > 10 ℃), high humidity (40%-60%) and slow wind (2 m/s) conditions prevailed for a long time in the Shenyang area. The unfavorable meteorological conditions lead to the occurrence of pollution. The backward trajectory showed that the potential source areas were concentrated in the urban agglomeration around Shenyang, and sporadic contributions came from North Korea.

Transport routes and potential source areas of PM10 in Kirklareli, Turkey.

In this study, the seasonal variation, transport routes, and potential source areas of PM10 in the central district of Kirklareli (Turkey) were investigated. It was determined that PM10 concentrations had the highest seasonal average value in autumn and the lowest seasonal average value in spring. Cumulative distributions of PM10 concentrations data set were examined. In order to determine the air mass source and transport routes, the backward trajectories of the air masses obtained by using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model were run and cluster analysis, which is one of the multivariate statistical analyses, was performed. Cluster analysis results revealed that there are five main clusters affecting the receptor site in all four seasons. By defining the PM10 concentrations data as an input to the potential source contribution function (PSCF) model, the probable locations of potential source areas were identified. It has been observed that there are obvious seasonal differences in the potential source areas of PM10. High PSCF values were observed especially in Greece and the Mediterranean during the winter and especially in Albania and Greece during the spring. While high PSCF values were observed especially in the Anatolian side of Istanbul, Kocaeli, Sakarya, and the Black Sea coasts of these regions during the summer, they were observed especially in Izmir and Balikesir during the autumn.

Temporal and spatial pattern of dust storms, their polycyclic aromatic hydrocarbons, and human health risk assessment in the dustiest region of the world.

This study evaluated the concentration and health risks of polycyclic aromatic hydrocarbons (PAHs) in Abadan City under 4 different climatic conditions: normal days, dusty days, dust with northwesterly winds, and dust with southeasterly winds. It also determined the sources of aromatics and discussed the relationship between meteorological parameters and PAH concentrations. The spatiotemporal distribution of dust in the area was determined using the HYSPLIT (hybrid single-particle Lagrangian integrated trajectory) back trajectory model, moderate resolution imaging spectroradiometer (MODIS) images. For this purpose, sampling was performed for 70 days using an Omni device. The concentrations of 16 PAHs (USEPA) ranged from 46.22 to 90.96 ng/m3. The highest concentration of high molecular weight (HMW) PAHs was 4-6 rings, of which 4 rings were predominant in all samples. PAH sources were identified using diagnostic ratios and principal component analysis (PCA), and it was shown that PAHs mainly originate from a mixture of sources, including vehicular emissions, petrol emissions, and traffic. Wind speed was negatively correlated with dust, except on dusty days. This result indicates a decrease in PAH concentrations when wind speed increases. On the other hand, the dust correlation with PAH was positive on normal days, but a negative correlation was observed on dusty days. This result was due to the lower concentration of PAHs from natural resources (such as dust source areas) vs. human resources (such as traffic and industry). PAH health risk assessment in Abadan City showed that the risk of carcinogenesis was higher on normal days and through skin contact. The probability of incremental lifetime cancer risk (ILCR) in all sampling conditions was potential in terms of carcinogenic risk (10-4-10-6). As a critical risk factor, relevant authorities should prevent, control, and reduce it.

Characteristics of equivalent black carbon aerosols over Doon Valley in NW Indian Himalaya during COVID-19 lockdown 2020.

Recently, black carbon (BC) has been identified as a potential transmitter for COVID-19 besides being responsible for climate change and serious health hazards. To mitigate the dreaded consequences of COVID-19 pandemic, the Government of India declared a nationwide lockdown on March 24, 2020. Accordingly, observations on equivalent black carbon (EBC) aerosols using AE 51 Aethalometer were performed during different lockdowns in Doon Valley. During April, May, June, and July, the monthly average EBC mass concentration recorded 2.12 ± 1.14 µg m-3, 2.58 ± 1.46 µg m-3, 2.74 ± 1.49 µg m-3, and 2.12 ± 1.32 µg m-3, respectively. A comparison of diurnal variation patterns with earlier studies indicates a significant reduction in EBC mass concentration levels. Bipolar NWR analysis for April and May depicts that relatively high EBC concentration was experienced with prominent south-easterly winds. The EBC concentration level during daytime was high compared to nighttime hours. Preliminary visualization of scanning electron micrographs indicates the variable morphology of aerosols. The bulk particle EDX spectral analysis indicates C, O, Na, F, Al, Si, K, Ca, and Ti elements with a dominance of C and O. Windblown dust seems to be the major contributor to the ambient aerosols. Furthermore, MODIS recorded the fire anomaly (attributed to the wheat stubble burning) starting from mid of April to early-June along the Indo-Gangetic Basin. Heavy loading of polluted aerosols was visible in CALIPSO data imageries. HYSPLIT cluster trajectories indicate that the study region is strongly influenced by the air mass transporting from the Gangetic Plain, Iran, Pakistan, Afghanistan, and Gulf region.

Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions.

The unprecedented outbreak of COVID-19 significantly improved the atmospheric environment for lockdown-imposed regions; however, scant evidence exists on its impacts on regions without lockdown. A novel research framework is proposed to evaluate the long-term monthly spatiotemporal impact of COVID-19 on Taiwan air quality through different statistical analyses, including geostatistical analysis, change detection analysis and identification of nonattainment pollutant occurrence between the average mean air pollutant concentrations from 2018-2019 and 2020, considering both meteorological and public transportation impacts. Contrary to lockdown-imposed regions, insignificant or worsened air quality conditions were observed at the beginning of COVID-19, but a delayed improvement occurred after April in Taiwan. The annual mean concentrations of PM10, PM2.5, SO2, NO2, CO and O3 in 2020 were reduced by 24%, 18%, 15%, 9.6%, 7.4% and 1.3%, respectively (relative to 2018-2019), and the overall occurrence frequency of nonattainment air pollutants declined by over 30%. Backward stepwise regression models for each air pollutant were successfully constructed utilizing 12 meteorological parameters (R2 > 0.8 except for SO2) to simulate the meteorological normalized business-as-usual concentration. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model simulated the fate of air pollutants (e.g., local emissions or transboundary pollution) for anomalous months. The changes in different public transportation usage volumes (e.g., roadway, railway, air, and waterway) moderately reduced air pollution, particularly CO and NO2. Reduced public transportation use had a more significant impact than meteorology on air quality improvement in Taiwan, highlighting the importance of proper public transportation management for air pollution control and paving a new path for sustainable air quality management even in the absence of a lockdown.

Transboundary sources dominated PM2.5 in Thimphu, Bhutan.

This study estimates the potential source regions contributing to PM2.5 in the capital city of Thimphu, Bhutan, during the years 2018-2020 using the ground-based data, followed by the HYSPLIT back trajectory analysis. The average PM2.5 concentration in the entire study period was 32.47 µg/m3 which is three times of the World Health Organization recommended limit of 10 µg/m3. Less than half of the days in pre-monsoon (43.47%) and post-monsoon (46.41%), and no days in winter were within the 24-h average WHO guideline of 25 µg/m3. During the COVID-19 lockdown imposed from August 11 to September 21 in Bhutan, only a marginal reduction of 4% in the PM2.5 concentrations was observed, indicating that nonlocal emissions dominate the PM2.5 concentrations in Thimphu, Bhutan. Most back trajectories in the analysis period were allocated to south or south-west sector. India was the major contributor (~ 44%), followed by Bangladesh (~ 19%), Bhutan itself (~ 19%) and China (~ 16%). This study confirms that there are significant contributions from transboundary sources to PM2.5 concentrations in Thimphu, Bhutan, and the elevated PM2.5 concentrations need to be tackled with appropriate action plans and interventions.

A general trait-based modelling framework for revealing patterns of airborne fungal dispersal threats to agriculture and native flora.

Fungal plant pathogens are of economic and ecological importance to global agriculture and natural ecosystems. Long-distance atmospheric dispersal of fungal spores (LAD) can pose threats to agricultural and native vegetation lands. An understanding of such patterns of fungal spore dispersal and invasion pathways can provide valuable insights into plant protection. Spore traits affect their dispersal abilities. We propose a general trait-based framework for modelling LAD to reveal dispersal patterns and pathways, and assess subsequent threats of arrival (TOA) quantitatively in the context of biosecurity. To illustrate the framework, we present a study of Australia and its surrounding land masses. The overall dispersal pattern covered almost the entire continent of Australia. Fungal spores in the size class of 10 and 20 µm (aerodynamic diameter) posed the greatest TOA. Our study shows the effects of morphological traits on these potential TOA, and how they varied between source regions, size classes, and seasons. Our framework revealed spore dispersal patterns and pathways. It also facilitates comparisons of spatio-temporal dispersal dynamics among fungal classes, gaining insights into atmospheric long-distance dispersal of fungi as a whole, and provides a basis for assessing fungal pest threats in potential source regions based on easily measured spore characteristics.

Impact of aerosols on surface ozone during COVID-19 pandemic in southern India: A multi-instrumental approach from ground and satellite observations, and model simulations.

The World Health Organization (WHO) declared the coronavirus disease of 2019 (COVID-19) as a pandemic due to its widespread global infection. This has resulted in lockdown under different phases in many nations, including India, around the globe. In the present study, we report the impact of aerosols on surface ozone in the context of pre-lockdown (01st - 24th March 2020 (PLD)), lockdown phase1 (25th March to 14th April 2020 (LDP1)), and lockdown phase 2 (15th April to 03rd May 2020 (LDP2)) on clear days at a semi-arid site, Anantapur in southern India using both in situ observations and model simulations. Collocated measurements of surface ozone (O3), aerosol optical depth (AOD), black carbon mass concentration (BC), total columnar ozone (TCO), solar radiation (SR), and ultraviolet radiation (UV-A) data were collected using an Ozone analyzer, MICROTOPS sunphotometer, Ozonometer, Aethalometer, and net radiometer during the study period. The diurnal variations of O3 and BC exhibited an opposite trend during three phases. The concentrations of ozone were ~10.7% higher during LDP1 (44.8 ± 5.2 ppbv) than the PLD (40.5 ± 6.0 ppbv), which mainly due to an unprecedented reduction in NOx emissions leading to a lower O3 titration by NO. The prominent increase in the surface zone during LDP1 is reasonably consistent with the observed photolysis frequencies (j (O1D)) through Tropospheric Ultraviolet and Visible (TUV) model. The results show that a pronounced spectral and temporal variability in the AOD during three lockdown phases is mainly due to distinct aerosol sources. The increase in AOD during LDP2 due to long-range transport can bring large amounts of mineral dust and smoke aerosols from the west Asian region and central India, and which is reasonably consistent with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories and Moderate Resolution Imaging Spectroradiometer (MODIS) fire counts analysis over the measurement location. Overall, a drastic reduction in BC concentration (~8.4%) and AOD (10.8%) were observed in the semi-arid area during LDP1 with correspondence to PLD. The columnar aerosol size distributions retrieved from the spectral AODs followed power-law plus unimodal during three phases. The absorption angstrom exponent (AAE) analysis reveals a predominant contribution to the BC from biomass burning activities during the lockdown period over the measurement location.

COVID-19 pandemic in Wuhan: Ambient air quality and the relationships between criteria air pollutants and meteorological variables before, during, and after lockdown.

As a result of the lockdown (LD) control measures enacted to curtail the COVID-19 pandemic in Wuhan, almost all non-essential human activities were halted beginning on January 23, 2020 when the total lockdown was implemented. In this study, changes in the concentrations of the six criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) in Wuhan were investigated before (January 1 to 23, 2020), during (January 24 to April 5, 2020), and after the COVID-19 lockdown (April 6 to June 20, 2020) periods. Also, the relationships between the air pollutants and meteorological variables during the three periods were investigated. The results showed that there was significant improvement in air quality during the lockdown. Compared to the pre-lockdown period, the concentrations of NO2, PM2.5, PM10, and CO decreased by 50.6, 41.2, 33.1, and 16.6%, respectively, while O3 increased by 149% during the lockdown. After the lockdown, the concentrations of PM2.5, CO and SO2 declined by an additional 19.6, 15.6, and 2.1%, respectively. However, NO2, O3, and PM10 increased by 55.5, 25.3, and 5.9%, respectively, compared to the lockdown period. Except for CO and SO2, WS had negative correlations with the other pollutants during the three periods. RH was inversely related with all pollutants. Positive correlations were observed between temperature and the pollutants during the lockdown. Easterly winds were associated with peak PM2.5 concentrations prior to the lockdown. The highest PM2.5 concentrations were associated with southwesterly wind during the lockdown, and northwesterly winds coincided with the peak PM2.5 concentrations after the lockdown. Although, COVID-19 pandemic had numerous negative effects on human health and the global economy, the reductions in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits. This study improves the understanding of the mechanisms that lead to air pollution under diverse meteorological conditions and suggest effective ways of reducing air pollution in Wuhan.

Identification of origins and influencing factors of environmental odor episodes using trajectory and proximity analyses.

It is challenging for the governmental agencies to provide an instant response and to systematically analyze the huge number of odor complaints which are received frequently by them. This study aimed to establish a data analysis framework featuring trajectory and proximity analyses to confirm odor origins, assess impact areas, and identify determinants and mechanisms of odor episodes based on odor reports. The investigation used 273 odor complaints reported in northern Collierville, Tennessee, between January 1st, 2019 and December 15th, 2020. The location of each complaint was geocoded in Google Map, and the backward wind trajectories were calculated using the web-based Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The nearby Eplex Landfill and Collierville Northwest Sewage Treatment Plant were targeted for the analyses. Odor impacts were evaluated with temporal and spatial characteristics of reported odor episodes. Logistic models were performed to identify weather parameters that significantly influenced odor occurrence. The field inspections indicated two periods targeting different sources. Period 1: from January 1st, 2019 to October 31st, 2020, the landfill appeared as the major source; Period 2: from November 1st, 2020 to December 15th, 2020, the sewage plant emerged as the major source. In Period 1, 65% of the complaints had wind transporting from the landfill, and 88% occurred at residences within 500 m of the landfill. In Period 2, 33% of the complaints had wind that blew from the sewage plant and 85% occurred at residences within 1000 m from the sewage plant. The likelihood of an odor episode day was significantly associated with wind speed [Odds Ratio (OR) = 0.66, 95% Confidence Interval (CI): 0.56-0.77], temperature (OR = 0.97, 95% CI: 0.95-0.98), and rainfall (OR = 1.02, 95% CI: 1.00-1.04). The odor issue in Collierville reflected poor zoning between the odor sources and residential areas. Separation distances of 500 m and 1000 m from the landfill and sewage facilities, respectively, are suggested to prevent odor issues. The proposed data analysis framework can be adopted by governmental agencies for fast responses to odor complaints, odor assessment, and environmental odor management.

Ambient ozone over mid-Brahmaputra Valley, India: effects of local emissions and atmospheric transport on the photostationary state.

This study presents the characteristics of ground level atmospheric ozone (O3) over the rural mid-Brahmaputra Valley region of the northeastern India. Ozone and oxides of nitrogen (NOx = NO + NO2) concentration data were obtained from continuous measurement of O3 and NOx housed at the MAPAN-AQM station at Tezpur University. The meteorological parameters were obtained from the same station. The diel, monthly, and seasonal variations of O3 were studied. The O3-NOx photostationary state (PS) was carefully examined and it was found that the net O3 concertation deviated substantially from the PS during the winter season. The deviation could be attributed to local biomass burning, biogenic VOC emission from forest and agriculture, and long-range transport of peroxyacyl nitrate (PAN). The long-range transport has been ascertained by examining the ventilation coefficients (VC), which correlated with the steep growth of net O3 concentrations in the morning hours. The HYSPLIT air mass back trajectories were used in concentration-weighted trajectory (CWT) analyses of O3 to assess the long-range regional transport of O3 precursors, which positively influenced local O3 concentrations.

Influence of meteorology, mobility, air mass transport and biomass burning on PM2.5 of three north Indian cities: phase-wise analysis of the COVID-19 lockdown.

Recent studies concluded that air quality has improved due to the enforcement of lockdown in the wake of COVID-19. However, they mostly concentrated on the changes during the lockdown period, and the studies considering the consequences of de-escalation of lockdown are inadequate. Therefore, we investigated the changes in fine particulate matter (PM2.5) during the pre-lockdown, strict lockdown, unlocking, and post-lockdown scenarios. In addition, we assessed the influence of meteorology, mobility, air mass transport, and biomass burning on PM2.5 using Google's mobility data, back trajectory model, and satellite-based fire incident data. Average PM2.5 concentrations in Ghaziabad, Noida, and Faridabad decreased by 60.70%, 63.27%, and 60.40%, respectively, during the lockdown. When compared with the preceding year (2019), the reductions during the shutdown period (25 March-31 May) were within the range of 36.34-44.55%. However, considering the entire year, this reduction in PM2.5 is momentary, and a steady increase in traffic density and industrial operations within cities during post-lockdown reflects a potent recovery of aerosol level, during which the average mass of PM2.5 three- to four-folds higher than the lockdown period. Back trajectories and fire activity results showed that biomass burning in the nearby states (Haryana and Punjab) influence aerosol load. We conclude that a partial lockdown in the event of a sudden surge in pollution would be a beneficial approach. However, reducing fossil fuel consumption and switching to more environmentally friendly energy sources, developing green transport networks, and circumventing biomass burning are efficient ways to improve air quality in the long term.

Medium- and long-range transport events of Alnus pollen in western Mediterranean.

Alnus pollen has been frequently detected in the atmosphere of different airborne sampling sites of Southern Spain. However, Alnus sp. populations are very scarce and fragmented in the area, being restricted to a few river valleys in the southwest, and other further away regions of the Iberian Peninsula. This leads to think that the airborne pollen detected could be mainly the result of a medium- or long-distant transport. So, the aim of this study was to characterize the annual patterns of airborne Alnus pollen detected at three different locations of Malaga province, as well as to determine its possible origin, the pollen dispersion potential of these Alnus isolated populations, and their possible reproductive connectivity. Pollen sampling was conducted by means of three Hirst-type volumetric pollen traps. Samples were mounted and counted following the recommendations of the Spanish Aerobiology Network and the European Aeroallergen Society. The possible pollen sources were detected by means of a combination of meteorological information and backward air trajectories analysis. A high inter-annual variability in the annual pollen integrals was found in all the stations, favouring certain meteorological conditions a long-range transport and, therefore, causing the high concentrations detected in some specific days. Alnus pollen seems to have a heterogeneous origin with prevalence of the long-distant transport, which would suggest a possible reproductive connection among distant populations.