Pollution Scenarios Research Articles

Seasonal characteristics of atmospheric peroxyacetyl nitrate (PAN) in a coastal city of Southeast China: Explanatory factors and photochemical effects

Abstract. Peroxyacetyl nitrate (PAN) acting as a typical indicator of photochemical pollution can redistribute NOx and modulate O3 production. Coupled with the observation-based model (OBM) and a generalized additive model (GAM), the intensive observation campaigns were conducted to reveal the pollution characteristics of PAN and its impact on O3, the contributions of influencing factors to PAN formation were also quantified in this paper. The F values of GAM results reflecting the importance of the influencing factors showed that ultraviolet radiation (UV; F value = 60.64), Ox (Ox = NO2 + O3, 57.65), and air temperature (T, 17.55) were the main contributors in the PAN pollution in spring, while the significant effects of Ox (58.45), total VOCs (TVOCs, 21.63), and T (20.46) were found in autumn. The PAN formation rate in autumn was 1.58 times higher than that in spring, relating to the intense photochemical reaction and meteorological conditions. Model simulations revealed that acetaldehyde oxidation (46 %±4 %) contributed to the dominant formation pathway of PA (hence PAN), followed by methylglyoxal oxidation (28 %±3 %) and radical cycling (19 %±3 %). The PAN formation was highly VOC sensitive, as surplus NOx (compared with VOCs abundance) prevented NOx from being the limiting factor photochemical formation of secondary pollution. At our site, PAN promoted and inhibited O3 formation under high and low ROx levels, respectively. The PAN promoting O3 formation mainly occurred during the periods of 11:00–16:00 (local time) when the favourable meteorological conditions (high UV and T) stimulated the photochemical reactions to offer ROx radicals, which accounted for 17 % of the whole monitoring periods in spring and 31 % in autumn. The analysis of PAN formation mechanism and its positive or negative effect on ozone provided scientific insights into photochemical pollution mechanisms under various pollution scenarios in coastal areas.

Climate change and air pollution: Translating their interplay into present and future mortality risk for Rome and Milan municipalities

Heat and cold temperatures associated with exposure to poor air quality lead to increased mortality. Using a generalized linear model with Poisson regression for overdispersion, this study quantifies the natural-caused mortality burden attributable to heat/cold temperatures and PM10 and O3 air pollutants in Rome and Milan, the two most populated Italian cities. We calculate local-specific mortality relative risks (RRs) for the period 2004–2015 considering the overall population and the most vulnerable age category (≥85 years). Combining a regional climate model with a chemistry-transport model under future climate and air pollution scenarios (RCP2.6 and RCP8.5), we then project mortality to 2050.Results show that for historical mortality the burden is much larger for cold than for warm temperatures. RR peaks during wintertime in Milan and summertime in Rome, highlighting the relevance of accounting for the effects of air pollution besides that of climate, in particular PM10 for Milan and O3 for Rome. Overall, Milan reports higher RRs while, in both cities, the elderly appear more susceptible to heat/cold and air pollution events than the average population. Two counterbalancing effects shape mortality in the future: an increase associated with higher and more frequent warmer daily temperatures – especially in the case of climate inaction – and a decrease due to declining cold-mortality burden. The outcomes highlight the urgent need to adopt more stringent and integrated climate and air quality policies to reduce the temperature and air pollution combined effects on health.

A study on water pollution scenario of the Damodar river basin, India: assessment of potential health risk using long term database (1980–2019) and statistical analysis

The present work deals with a detailed study of India's Damodar river basin's pollution profile (groundwater, surface water, industrial water, and mine water). The present paper aims to create a large data bank comprising the latest (2019; through water sampling and analysis) and historical (1980-2018; through literature survey) data on heavy metal loads (HML) and other hydrochemical parameters in water bodies of the Damodar basin (at 99 sampling locations). Bivariate and multivariate statistical analyses were applied to determine the possible sources of the HML in the groundwater and surface water. Anthropogenic inputs from industrial effluents and mining activities were identified as the sources of the HML. The degree of HML exposure (Fe, Cu, Zn, Mn, As, Co, Cd, Hg, Cr, Ni, and Cu) was considered for computing the heavy metal pollution indices (HMPI). Associated potential health risk to the local population was also studied. Most HMPIs (vary within 50-9000) appeared to cross the critical value (~ 100). According to the results of noncarcinogenic risk, most hazard indices (varied within 0.01-116.34) surpassed the allowable limit (~ 1), demonstrating detrimental health effects on adults and children. Ni, Cd, As, and Cr showed very high cancer indices (varied within 9.5 × 10-5-1.76 × 10-1) that could be considered as high risk (≫ 1 × 10-4, allowable limit) for cancer via ingestion and dermal pathways. A carcinogenic risk assessment map of the basin was also prepared for the first time. Durgapur and Burnpur-Asansol cities have been identified as the most vulnerable areas. The authors also compared the water quality parameters of the Damodar river with other highly polluted and major rivers of India. The authors recommended (i) strict regulation and efficient management of HML monitoring, (ii) initiating public awareness programme about Damodar's pollution, and (iii) a detailed medical survey to understand the impact of water pollution on the population.

Simulated multispectral temperature and atmospheric composition retrievals for the JPL GEO-IR Sounder

Abstract. Satellite measurements enable quantification of atmospheric temperature, humidity, wind fields, and trace gas vertical profiles. The majority of current instruments operate on polar orbiting satellites and either in the thermal and mid-wave or in the shortwave infrared spectral regions. We present a new multispectral instrument concept for improved measurements from geostationary orbit (GEO) with sensitivity to the boundary layer. The JPL GEO-IR Sounder, which is an imaging Fourier transform spectrometer, uses a wide spectral range (1–15.4 µm) encompassing both reflected solar and thermal emission bands to improve sensitivity to the lower troposphere and boundary layer. We perform retrieval simulations for both clean and polluted scenarios that also encompass different temperature and humidity profiles. The results illustrate the benefits of combining shortwave and thermal infrared measurements. In particular, the former adds information in the boundary layer, while the latter helps to separate near-surface and mid-tropospheric variability. The performance of the JPL GEO-IR Sounder is similar to or better than currently operational instruments. The proposed concept is expected to improve weather forecasting as well as severe storm tracking and forecasting and also benefit local and global air quality and climate research.

Experimental Investigation on Bioremediation of Heavy Metal Contaminated Solution by Sporosarcina pasteurii under Some Complex Conditions

Bioremediation of contaminated solutions has attracted extensive attention in recent years due to its wide range of applicability to various types of contaminants and environmental friendliness. Previous studies adequately confirmed the potential of Sporosarcina pasteurii (i.e., S. pasteurii)-based bioremediation for heavy metal contaminated solutions, but they focused mainly on the bioremediation ability of single-heavy-metal contaminated solutions. This study focuses on S. pasteurii-based bioremediation under more complex pollution conditions. A series of laboratory experiments were performed to explore the efficiency and mechanism of S. pasteurii-based bioremediation to heavy metal contaminated solutions under various conditions, including single-heavy-metal pollution condition, heavy metal pollution under high mineral salinity context and multi-heavy-metal pollution scenarios. The results show that S. pasteurii can effectively remove heavy metals such as Cd, Cr(III), and Zn through biomineralization; for the typical range of mineral salinity (including NaCl and KCl) possibly encountered in practice in some contaminated solutions, such as leachate of landfills, the detrimental influence of high mineral salinity on efficiency of S. pasteurii-based bioremediation can be neglected; more importantly, S. pasteurii-based bioremediation can be considered as a potential option for remedying multi-heavy-metal contaminated solutions, though the addition of some heavy metals tends to produce a substantially detrimental influence on the bioremediation ability of S. pasteurii to other heavy metals.

Biomonitoring and assessment of airborne fluoride using Lolium perenne near a phosphate fertilizer production facility

Airborne fluoride emission is an environmental concern. There is a lack of knowledge in determining factors influencing internal fluoride accumulation in plant tissue. The aim of this study was to improve understanding of how temporal, spatial and physiological factors influence internal fluoride accumulation. Lolium perenne L. (perennial rye grass) was used as a bioindicator and exposed in 52 sites in 2015 and 11 sites in 2016 surrounding the emission source. Biomass was harvested for fluoride analysis. A biomonitoring system was developed to standardize greenhouse cultivation, field exposure, and plant harvest. Results show that relatively cooler weather may promote internal fluoride accumulation of perennial rye grass over time. Distance from the source and exposure time significantly influenced internal fluoride accumulation. Internal fluoride concentrations decreased exponentially with distance from the source, with a sharp drop within 500 m. Generally, fluoride accumulation increased with days of exposure. It peaked after 81 days of exposure in 2015 and 110 days in 2016. Plant age had no significant impact on fluoride accumulation. Biomonitoring can be a cost effective approach for detecting long term environmental impacts of airborne pollution. The method in this research can be applied in various point source air pollution scenarios to assess emission impacts on biota and to aid in land use management.

Трехмерная математическая модель прогнозирования загрязнения водного объекта биогенными элементами

The article presents the results of the development of three-dimensional modeling and the results of forecasting the pollution of a water body with biogenic elements on the example of the Pekhorka River in the Balashikhinsky district of the Moscow region. To solve the problem of improving the environmental safety of the river basin, a mathematical three-dimensional model for predicting pollution by biogenic elements has been developed. As an assessment of the pollution of the Pekhorka River, the method of assessing the impact on the indicator of chemical pollution was chosen. The development of a mathematical model of pollutant transport was carried out using the Python Version 3.8 programming environment. The mathematical models considered two scenarios of river pollution: actual river pollution with biogenic pollutants and forecast pollution. As a result of modeling, the nature of mixing and longitudinal dispersion along the river fl ow was determined. It was found that vertical mixing occurs quite quickly at a distance of several depths of the river, lateral mixing occurs much slower, but usually ends within a few kilometers downstream. Three-dimensional mathematical models for predicting water body pollution are designed to quantify the dynamic processes of mass transfer in space and time and allow solving problems of environmental safety of catchment areas and water bodies.

Environmental and ecotoxicological risk assessment of pollution with light crude oil for an oil exploatation field

Global development of transportation dependent on internal combustion engines, involves major increases in the consumption of fossil fuels obtained by extracting crude oil from depths by means of wells and refining it. In this context, protection of environment and groundwater quality is an increasingly difficult objective to maintain, requiring modern methods to address possible negative effects on the environment. The current research assesses the degree of eco-toxicological and environmental risk for an oil exploitation area in case of an accidental pollution scenario with crude oil. The entire risk spectrum was analysed through a set of qualitative and quantitative risk assessment tools to highlight and quantify the most important effects caused by petroleum products on biotope and biocenoses. The primary aim of the research is to identify vulnerable environmental reservoirs for accidental oil pollution and to establish the best tools to quantify the environmental and ecotoxicological risk of groundwater contamination. The results obtained from the area showed a low to medium risk of contamination of the saturated and unsaturated area with crude oil expressed as TPH (total petroleum hydrocarbons) and a low risk of contamination with volatile organic compounds type BTEX associated contamination of biocenoses that can directly or indirectly interact with potentially polluted areas.

Air pollution in three megacities of India during the Diwali festival amidst COVID-19 pandemic

• Seven air pollutant levels were analyzed during Diwali in three megacities of India. • Scenario of Diwali 2019 (non-pandemic) and Diwali 2020 (amidst pandemic) was compared. • Pre-Diwali to Diwali changes in air pollutant levels were highest in Delhi. • Mumbai and Kolkata exhibited minimal increase in pollutant levels during Diwali 2020. • Unfavorable meteorological conditions worsened the air pollution scenario in Delhi. The present study characterized the difference in air pollution levels between Diwali celebrations amidst the Covid-19 pandemic (14 November 2020) and the previous year (27 October 2019). The concentration of seven principal air pollutants, namely PM 2.5 , PM 10 , NO 2 , NH 3 , SO 2 , CO, and O 3 , was substantially higher in 2020 Diwali than in 2019 Diwali. PM 2.5 , PM 10 , and CO were always above the permissible limits in all three megacities, with the highest concentrations observed in Delhi. This observation indicates that amidst the pandemic, people burnt more firecrackers than the preceding year. However, the pre-Diwali to Diwali changes in pollutant concentrations suggested that Mumbai and Kolkata had lower pollution levels due to the fireworks. The firework-induced air pollutant load in Delhi was enhanced by a higher margin in the pandemic year. The difference in meteorological conditions between the two consecutive year's Diwali might have led to the enhanced pollutant load in 2020, especially in Delhi. Delhi showed a tendency to retain the pollutants in the ground-level atmosphere for almost one week after the event. Thus, this study implies the need for stringent law enforcement to ameliorate the pollution levels due to such celebrations.

Air pollution scenario analyses of fleet replacement strategies to accomplish reductions in criteria air pollutants and 74 VOCs over India

Traffic emissions are a major source of air pollution and associated damage to human health in India. Many of the Indian metro cities urgently require cleaner transportation technologies to ensure cleaner air. Here, using newly compiled spatially disaggregated, gridded, high-resolution (0.1° × 0.1°) road transport emission inventory for India for 2030 (RTEII) of 74 speciated VOCs, CO, SO 2 , NOx, NH 3 , CH 4 , CO 2, BC, OC and PM 2.5 from varied fuels and vehicle technologies that are currently in use in India, we investigated changes in emission in response to substitution of the existing vehicular fleet by cleaner alternatives. Three “what-if” intervention scenarios were considered to assess the extent in improvement of air quality due to the reduction in the primary emission of air pollutants. The results show that significant reductions in direct emission of pollutants (Non-Methane VOCs, −91%; CO, −80%; PM 2.5 , 44%) including toxic VOCs (e.g., isocyanic acid, −76%; BTEX, −93%; as well as individual VOC classes (e.g., sum of OVOCs, −61% and sum of alkenes, −80%) can likely be achieved in 2030 by shifting from highly polluting Internal Combustion Engine (ICE) based 2 and 3-wheeled vehicles to Electric Vehicles (EVs) under scenario 1. The amount of secondary pollutants such as SOA and O 3 that can potentially be formed from traffic also showed significant reduction of 94% and 84%, respectively, under scenario 1. Conversion of diesel fuelled vehicles to CNG under scenario 2 can lead to a larger reduction in black carbon emissions (−50%). Scenario 3, in which the benefits of scenarios 1 and 2 are combined, represents the best long-term strategy moving forward, which can result in massive emission reductions of pollutants through existing technologies of greener transport fleets over India. Large scale conversion of the vehicle fleets as explored here can lead to a substantial reduction of air pollution and fewer lives lost. • Study examines 2030 road-transport emission reductions for India. • Three “what-if” intervention scenarios with electric vehicles and greener fuels. • 2&3-wheeler vehicles replacement by EVs reduced NMVOC emissions by 91%. • Conversion of diesel fuelled vehicles to CNG reduced primary BC by 50%. • Combining EVs and diesel to CNG for HDVs can improve air quality over India greatly.

Groundwater Pollution in Bangladesh: A Review

Bangladesh relies mainly on groundwater for irrigation and drinking purposes. Groundwater, however, continuously polluted, is a major obstacle. Nowadays, Bangladesh is moving towards industrial revolution in a considerable speed. As part of this paper's attempt to analyze the groundwater pollution scenario in Bangladesh, specifically in the past two decades, about 100 articles, conference papers, and reports published in national and international journals and books were reviewed, as well as issues concerning pollution sources, health impact assessment, and future perspectives were discussed. The groundwater is contaminated by different contaminants, such as physico-chemicals, trace metals, and microbes. Human health is at great risk from arsenic (As) contamination; it is one of the biggest threats. The cancer risk and non-cancer risk of ingesting water are increased. On the other hand, a large number of peoples were affected due to waterborne diseases governed by microbial contamination. Geophysical and anthropogenic sources, the depth of wells, and geographical factors may influence groundwater pollution. It is recommended that policy makers should address the issue immediately and precautions should be taken wherever necessary.

Physics experiments using arduino: determination of the air quality index

Air pollution is one of our day’s significant reasons for human health problems and affects every community throughout the world. Monitoring air pollution is a key aspect of raising awareness and pollution mitigation approaches followed by different nations. This paper targets to develop a low-cost Internet of things-based embedded system to measure and maintain air quality index (AQI) indicators at any locality. The system implemented here is minimal and can be deployed quickly and easily. The AQI measurement system was developed and tested for several periods, and recorded values of AQI were found to be in close agreement with actual values obtained from standard databases. In addition, several starting physics and electronics laboratory courses train students on measuring physical parameters over time. In this context, along with the introduction to the current pollution scenario and the challenges, this experiment will give a first-hand exposure of setting up a simple experiment and measuring a physical parameter to time. Students also learn to write simple programs and interface the experiment with a computer to record the results. The current work also demonstrates how to publish/subscribe the data using the message queue telemetry transport protocol.

Road traffic noise assessment in a hospital area in Umuarama - Brazil

In hospital environments, high noise levels can result in damage to patients' treatments, delaying their rest and recovery. The sound pressure level (SPL) in hospital areas during the day must not exceed 50 dB and 45 dB (A) at night, according to NBR 10.151/2019. This research aimed to carry out environmental monitoring of equivalent sound pressure levels (LAeq) at fifteen points in the vicinity of three hospitals in the central region of the municipality of Umuarama-PR, during working days, at four different times, in the months of August, September and November 2018 and continued in March 2019. To this end, we sought to map the LAeq of the points, compare them with data from municipal and federal legislation and relate the LAeq to the volume of vehicular traffic. The collected SPL were higher than recommended by NBR 10.151 at all times and measurement points, during the week, and when considering the municipal regulations, only one point is in the equipment's accuracy limit. From the statistical analysis, a very strong correlation was observed between LAeq and the total volume of vehicles, and also a strong correlation between the descriptors L10 and L50 and the volume of vehicles. The Traffic Noise Index (TNI) was also calculated and the LAeq values ​​were compared with a subjective noise rating. The results show a scenario of noise pollution in the area and there is a need for the application of mitigating measures.

Reservoir operation under accidental MTBE pollution: A graph-based conflict resolution framework considering spatial-temporal-quantitative uncertainties

Given the hazardous effects of sudden dam reservoir contamination — as might occur upon the intrusion of the fuel additive methyl tert-butyl ether (MTBE) — the contaminant’s effect on the quality of allocated waters requires careful study. Employed to determine optimal reservoir operational rules in the case of sudden MTBE pollution, a risk-based simulation–optimization model was developed to simultaneously minimize unsatisfied water demand, the risk of violations of water quality standards, and the reservoir recovery time. Risks were assessed by considering various often-neglected pollution scenarios as a combination of location, quantity, and the season of pollution intrusion. The appropriateness of operational rules proved to depend upon thermal conditions and MTBE intrusion properties, confirming the necessity of considering location-quantity-season uncertainties. Social and regional conditions also occupied a dominant role in determining the level of satisfaction achieved under different water allocation strategies. Accordingly, by considering environmental conditions and local rules, a graph model for conflict resolution was established and used to reach a set of compromise operational rules. The developed framework could serve as a guide for water utilities to determine efficient reservoir operational rules after a sudden contaminant intrusion.

Pesticide Use in Bangladesh: A Review on Potential Impacts

Bangladesh is a densely populated agricultural country. A wide range of products of pesticides being used in Bangladesh is already considered a health and environmental concern by different international agencies including the World Health Organization (WHO). Excessive, irrational use of pesticides in agriculture, and lack of knowledge on pest management have caused widespread pesticide pollution which is now posing a substantial threat to the environment and local people. In this review, we assessed and analyzed previous literature systematically to map a complete scenario of pesticide pollution in Bangladesh, covering soil, water, and foods. Most of the previous studies indicated that soil, water, and different seasonal vegetables are contaminated with organophosphorus, pyrethroid, and exceeded the FAO/WHO maximum residual limits. Concentration of chlorpyriphos, malathion were found below the detection limit in soil samples. But water samples were found contaminated with chlorpyrifos, diazinon, malathion, carbaryl and carbofuran. Considered vegetable samples were adulterated with fenvalerate, quinalphos, cypermethrin, fenitrothion, dimethoate, parathion, linuron, phenthoate. Persistence of organochlorines in the environment is limited and meets the maximum residue level (MRLs). This study will help to depict the pesticide pollution status in the environmental matrices in recent years and to cut off the exacerbation of pesticide pollution. A proactive approach is essential to limit the pesticide pollution load in the environmental matrices.

Spatially-structured human mortality modelling using air pollutants with a compositional approach

The human mortality models with a demographic approach are performed in function of time. The addition of information (social, economic, and environmental) in the structure of demographic models allows fitting observed values better. Air pollution influences human mortality and could be used as an environmental covariate in the demographic models. The levels of air pollutants describe quantitatively the parts of a whole (air), called composition, and their statistical treatment should consider this characteristic in the modelling process. This article evaluated the association between human mortality data with levels of air pollutants as a composition using a spatially-structured model. The spatially-structured modelling approach in the human mortality data captures the spatial heterogeneity of air pollutant concentrations (local environmental conditions). Human mortality data is defined as the number of deaths, and in this work, it was analyzed with both total and disaggregated presentation. The disaggregation was by (i) sex and (ii) sex and age-group. A likelihood ratio test suggested the model with air pollutants as covariates treated under a compositional approach (proposed model) is more appropriate than the model based only on time explanatory variable in yearly basis. The proposed model was evaluated in 48 counties in Spain, each with its mortality and air pollution dataset. The modelling approach in this work presented adequate quality model indexes and could be applied to make short-term predictions with different air pollution scenarios.

Orbit decay of 2–100 au planetary remnants around white dwarfs with no gravitational assistance from planets

ABSTRACT A widely held assumption is that each single white dwarf containing observable rocky debris requires the presence of at least one terrestrial or giant planet to have gravitationally perturbed the progenitor of the debris into the star. However, these planets could have been previously engulfed by the star or escaped the system, leaving behind asteroids, boulders, cobbles, pebbles, sand, and dust. These remaining small bodies could then persist throughout the host star’s evolution into a white dwarf at ≈2–100 au scales, and then be radiatively dragged into the white dwarf without the help of a planet. Here, we identify the parameter space and cooling ages for which this one metal-pollution mechanism is feasible by, for the first time, coupling Poynting–Robertson drag, the Yarkovsky effect, and the YORP effect solely from rapidly dimming white dwarf radiation. We find that this no-planet pollution scenario is efficient for remnant 10−5 to 10−4 m dust up to about 80 au, 10−4 to 10−3 m sand up to about 25 au, and 10−3 to 10−2 m small pebbles up to about 8 au, and perhaps 10−1 to 100 m small boulders up to tens of au. Further, young white dwarf radiation can spin-up large strengthless boulders with radii of 102–103 m to destruction, breaking them down into smaller fragments that then can be dragged towards the white dwarf. Our work hence introduces a planetless metal-pollution mechanism that may be active in some fraction of white dwarf planetary systems.

How do aerosols above the residual layer affect the planetary boundary layer height?

We revealed that the absorption aerosol lying below or above the morning residual layer (MRL) promotes (stove effect, heating the MRL layer) or strongly inhibits (dome effect, heating the temperature inversion layer) the development of planetary boundary layer (PBL) after sunrise, while scattering aerosol exhibits similar suppression (surface or aloft umbrella effect) on the PBL regardless of its vertical location. However, the role of different type of aerosols (i.e., strong absorption aerosol and purely scattering aerosol) present from MRL to upper atmosphere remains lacking and therefore, needs to be further explored. Utilizing a large-eddy simulation model constrained by the in-situ observations in urban Beijing, we observed that the dome inhibition of absorption aerosols on PBL development becomes weaker as elevating the aerosol layer, and the effect (virtual dome effect) remains no change beyond a certain height, which is defined as the dome effective height z. This height z is highly related to the surface sensible heat flux. By comparison, the altitude of light-scattering aerosols relative to the MRL was less important. The scattering aerosols exhibit similar inhibition from MRL to upper atmosphere (aloft umbrella effect), but to a weaker extent than the virtual dome effect. The virtual dome effect and aloft umbrella effect play a leading role during some extremely polluted scenarios with deep aerosol layer, such as sandstorms and volcanic eruptions. Aerosol dome, virtual dome, and aloft umbrella effects, together with aerosol stove and surface umbrella effects, further advance the understanding on aerosol-PBL interactions, which is, more broadly, applied to interpret the impact of aerosol on PBL over other ecosystems as well as exoplanet atmospheres.

An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe

Abstract. Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

Evaluation of Single Missing Value Imputation Techniques for Incomplete Air Particulates Matter (PM10) Data in Malaysia

The missing value in the dataset has always been the critical issue of accurate prediction. It may lead to a misleading understanding of the scenario of air pollution. There might only be a small number of missing (5% to 10%) answers to each problem, but the missing details may vary. This research is focused mainly on solving long gap missing data. Single missing value imputation means replacing blank space in the monitoring dataset from chosen Department of Environment (DoE) monitoring station with the calculated value from the best technique for long gap hours. The variable that is mainly being a monitor is PM10. The technique focused on this research is the single imputation technique. Furthermore, this technique was tested on the Tanjung Malim monitoring station dataset by fitting with five performance indicators. The result was compared with the previous study, whether it is the best used for long gap hour data. Four stages need to be followed to complete this research. The steps are data acquisitions, characteristic analysis of missing value, single imputation approach, verification of approach and suggestion of the best technique. This research used four existing imputation techniques: series mean (SM), mean of nearby points (MNP), linear trend (LT), and linear interpolation (LIN). This research shows that the interpolation technique is the best technique to apply particulate matter missing data replacement with the least mean absolute error and better performance accuracy.