The aim of this study was to assess air quality by using medium-cost sensors in recreational areas that are not covered by permanent monitoring. Concentrations of air pollutants PM2.5, PM10, PM1, CO, O ${}_3$ , NO ${}_2$ in the Niedzica recreational area in southern Poland were obtained. The research revealed that in cold weather, particulate matter concentrations significantly exceeded acceptable levels determined for PM2.5 and PM10. The most important factor that affects air quality within the studied area seems to be the combustion of poor quality fuels for heating purposes. The information obtained by the research presented could be a useful tool for local authorities to make environmental decisions, based on the potential health impacts of poor air quality levels on the population. Full article

Aerosol indirect effects on precipitation were investigated in this study using a Global/Regional Integrated Model system (GRIMs) linked with a chemistry package devised for reducing the heavy computational burden occurring in common atmosphere–chemistry coupling models. The chemistry package was based on the Goddard Chemistry Aerosol Radiation and Transport scheme of Weather Research and Forecasting with Chemistry (WRF-Chem), and five tracers that are relatively important for cloud condensation nuclei (CCN) formation were treated as prognostic variables. For coupling with the cloud physics processes in the GRIMs, the CCN number concentrations derived from the simplified chemistry package were utilized in the cumulus parameterization scheme (CPS) and the microphysics scheme (MPS). The simulated CCN number concentrations were higher than those used in original cloud physics schemes and, overall, the amount of incoming shortwave radiation reaching the ground was indirectly reduced by an increase in clouds owing to a high CCN. The amount of heavier precipitation increased over the tropics owing to the inclusion of enhanced riming effects under deep precipitating convection. The trend regarding the changes in non-convective precipitation was mixed depending on the atmospheric conditions. The increase in small-size cloud water owing to a suppressed autoconversion led to a reduction in precipitation. More precipitation can occur when ice particles fall under high CCN conditions owing to the accretion of cloud water by snow and graupel, along with their melting. Full article

Tropical cyclones and meiyu-baiu fronts, as the two main synoptic systems over East Asia, bring heavy rain during summers, but their long-term and vertical raindrop size distribution (RSD) features over the midlatitude Japan Islands are limited. Radar-based quantitative precipitation estimation (QPE) techniques require RSD observations. In this study, five-year observations from Tokyo with a ground-based impact Joss-Waldvogel disdrometer (JWD) and a vertically pointing micro rain radar (MRR) with a vertical range of 0.2–6.0 km were used to study the vertical structures of RSD and QPE parameters. The results showed that the convective rain associated with tropical cyclones had a maritime nature, while the rain associated with the meiyu-baiu front had a continental nature. The rain associated with tropical cyclones had a relatively higher concentration of raindrops and a larger average raindrop diameter than the rain associated with the meiyu-baiu front. The Z–R (radar reflectivity-rain rate) relationships (Z = AR^b) based on the JWD data for tropical cyclones, the meiyu-baiu front and total summer rainfall in Tokyo were Z = 189 R^1.38, Z = 214 R^1.35 and Z = 212 R^1.33, respectively. When the Z–R relationships obtained in this study were used to replace the operational relationship of Z = 300 R^1.4, the standard deviation of the rain rate was reduced from 5.50 mm/h (2.34 mm/h) to 2.34 mm/h (1.32 mm/h) for typhoon (meiyu-baiu front) rainfall, although the change for total summer rainfall was small. In addition, with increasing height below 4 km, the value of A and b decreased. Full article

Total precipitable water (TPW) of satellite-borne microwave radiometer retrievals is compared with the data that were collected from 49 island radiosonde stations for the period 2007–2015. Great consistency was found between TPW measurements made by radiosonde and eight satellite-borne microwave radiometers, including SSMI-F13, SSMI-F14, SSMIS-F16, SSMIS-F17, AMSR-E, AMSR-2, GMI, and WindSat. Mean values of the TPW differences for eight satellites ranged from −0.51 to 0.38mm, both root mean square errors and standard deviations were around 3mm, and all of the correlation coefficients between satellite TPW retrievals and radiosonde TPW for each satellite can reach 0.99. Subsequently, an analysis of the comparison results was conducted, which revealed three problems in the satellite TPW retrieval and two problems in radiosonde data. For TPW retrievals of satellite, when the values are above 60 mm, the precision of TPW retrieval significantly decreases with a distinct dry bias, which can reach 4 mm; additionally, abias related to wind speed and the uncertainty with the TPW retrieval in the presence of rain, which is stronger than 1mm/h, was found. The TPW measurements of radiosonde made by the type of IM-MK3 from India were quite unreliable, and almost all of the radiosonde data during the daytime were plagued by a dry bias. Full article

On the afternoon of 21 August 2017, a partial solar eclipse occurred over the Blue Ridge Mountains in central Virginia, USA. High-resolution meteorological observations were made on the floor of a small valley to investigate the effect of eclipse-induced cooling on thermally-driven winds. Measurements taken both at the surface and in the lower atmosphere indicate cooling throughout much of the atmospheric boundary layer. Multiple surface weather stations observed wind rotations that occurred both during and after the eclipse, as wind direction shifted from upvalley to downvalley and back to upvalley. The direction of these rotations (clockwise vs. counterclockwise) varied between stations and was strongly influenced by the proximity of the stations to topographic features in the valley. Doppler lidar observations over the valley floor show a 300 m thick layer of downvalley winds that formed below a deeper layer of upvalley winds. Changes in boundary layer winds and structure during the solar eclipse are similar to changes during the morning and evening transitions. However, the subtle differences in the direction of wind rotations between diurnal- and eclipse-transition periods provided important new insights into the interaction between slope- and valley flows, incoming solar radiation, and topographic features. Full article

The correlation of near-inertial wind stress (NIWS) in typhoon and typhoon-induced oceanic near-inertial kinetic energy (NIKE) in the upper South China Sea (SCS) is investigated through reanalysis data and an idealized typhoon model. It is found that the typhoon-induced oceanic near-inertial currents are primarily induced by the NIWS, which may contribute to about 80% of the total NIKE induced by typhoon. The intensities and distributions of NIWS in most typhoons are consistent with the magnitudes and features of NIKE. The NIWS and the NIKE along the typhoon track have positive correlations with the maximum wind speed of a typhoon, but there is an optimal translation speed for NIWS, at which the wind energy of the near-inertial band reaches its maximum. In the idealized typhoon model, a cluster of high-value centers of NIWS appear along the typhoon track, but there is only one high-value center for the near-inertial currents. The maximum NIWS arrives about 15 hours prior to the maximum near-inertial current. The distribution of NIWS is apparently asymmetric along the typhoon track, which may be due to the smaller eastward component of wind energy. Full article

Long-term gust speed (GS) measurements were used to develop a winter storm atlas of the 98 most severe winter storms in Germany in the period 1981–2018 (GeWiSa). The 25 m × 25 m storm-related GS fields were reconstructed in a two-step procedure: Firstly, the median gust speed ( $\widetilde{GS}$ ) of all winter storms was modeled by a least-squares boosting (LSBoost) approach. Orographic features and surface roughness were used as predictor variables. Secondly, the quotient of GS related to each winter storm to $\widetilde{GS}$ , which was defined as storm field factor (STF), was calculated and mapped by a thin plate spline interpolation (TPS). It was found that the mean study area-wide GS associated with the 2007 storm Kyrill is highest (29.7 m/s). In Southern Germany, the 1999 storm Lothar, with STF being up to 2.2, was the most extreme winter storm in terms of STF and GS. The results demonstrate that the variability of STF has a considerable impact on the simulated GS fields. Event-related model validation yielded a coefficient of determination (R²) of 0.786 for the test dataset. The developed GS fields can be used as input to storm damage models representing storm hazard. With the knowledge of the storm hazard, factors describing the vulnerability of storm exposed objects and structures can be better estimated, resulting in improved risk management. Full article

The effects of coupling between the atmospheric model of the Consortium for Small-Scale Modelling-Climate Limited-area Modelling (CCLM) and the wind wave model (WAM) on the lower atmosphere within the North Sea area are studied. Due to the two-way coupling between the models, the influences of wind waves and the atmosphere on each other can be determined. This two-way coupling between these models is enabled through the introduction of wave-induced drag into CCLM and updated winds into WAM. As a result of wave-induced drag, different atmospheric parameters are either directly or indirectly influenced by the wave conditions. The largest differences between the coupled and reference model simulation are found during storm events as well as in areas of steep gradients in the mean sea level pressure, wind speed or temperature. In the two-way coupled simulation, the position and strength of these gradients vary, compared to the reference simulation, leading to differences that spread throughout the entire planetary boundary layer and outside the coupled model area, thereby influencing the atmosphere over land and ocean, although not coupled to the wave model. Ultimately, the results of both model simulations are assessed against in situ and satellite measurements, with a better general performance of the two-way coupled simulation with respect to the observations. Full article

Recent regulatory and legislative developments in the state of California (e.g., Assembly Bill (AB) 1647 and AB 617) will increase the extent of air quality monitoring in communities near petroleum refineries and at facility fencelines. This work reports results over a three-year period for currently-installed community and fenceline air quality monitoring for the Chevron refinery in Richmond, California, USA. This paper presents the most comprehensive air quality dataset that has been published to date for a community near a petroleum refinery, including concentration of different air toxics (e.g., benzene, toluene, xylenes, etc.) and criteria air pollutants (e.g., ozone (O₃), sulfur dioxide (SO₂), and particulate matter (PM)). Instrumental techniques such as ultra-violet differential absorption spectroscopy (UV-DOAS), laser-based spectroscopy and real-time gas chromatography (GC) were used in the community and fenceline monitors. From 2015 to 2017, measured concentrations at community monitors near the Richmond refinery were generally below California thresholds for acute and chronic health (only two exceedances were observed for 8-h average benzene concentrations during the three-year monitoring period). Although more detailed speciation for volatile organic compounds (VOCs) and fine particulate matter (PM_2.5) would be needed to confirm certain source profile identities, preliminary application of source apportionment methods indicates the prevalence of typical urban emission profiles, such as from traffic, in the measured community data. Full article

Turbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) Observatory during two ShUREX (Shigaraki UAV Radar Experiment) campaigns in 2016 and 2017. The practical processing methods used for estimating turbulence kinetic energy dissipation rate $\epsilon$ and temperature structure function parameter $C_T^2$ from one-dimensional wind and temperature frequency spectra are first described in detail. Both are based on the identification of inertial (−5/3) subranges in respective spectra. Using a formulation relating $\epsilon$ and $C_T^2$ valid for Kolmogorov turbulence in steady state, the flux Richardson number $R_f$ and the mixing efficiency ${\chi }_m$ are then estimated. The statistical analysis confirms the variability of $R_f$ and ${\chi }_m$ around $~0.13-0.14$ and $~0.16-0.17$ , respectively, values close to the canonical values found from some earlier experimental and theoretical studies of both the atmosphere and the oceans. The relevance of the interpretation of the inertial subranges in terms of Kolmogorov turbulence is confirmed by assessing the consistency of additional parameters, the Ozmidov length scale $L_O$ , the buoyancy Reynolds number $R{e}_b$ , and the gradient Richardson number Ri. Finally, a case study is presented showing altitude differences between the peaks of $N^2$ , $C_T^2$ and $\epsilon$ , suggesting turbulent stirring at the margin of a stable temperature gradient sheet. The possible contribution of this sheet and layer structure on clear air radar backscattering mechanisms is examined. Full article

Volatile organic compounds (VOCs) are important precursors to the formation of ozone and fine particulate matter, the two pollutants of most concern in Sydney, Australia. Despite this importance, there are very few published measurements of ambient VOC concentrations in Australia. In this paper, we present mole fractions of several important VOCs measured during the campaign known as MUMBA (Measurements of Urban, Marine and Biogenic Air) in the Australian city of Wollongong (34°S). We particularly focus on measurements made during periods when clean marine air impacted the measurement site and on VOCs of biogenic origin. Typical unpolluted marine air mole fractions during austral summer 2012-2013 at latitude 34°S were established for CO₂ (391.0 ± 0.6 ppm), CH₄ (1760.1 ± 0.4 ppb), N₂O (325.04 ± 0.08 ppb), CO (52.4 ± 1.7 ppb), O₃ (20.5 ± 1.1 ppb), acetaldehyde (190 ± 40 ppt), acetone (260 ± 30 ppt), dimethyl sulphide (50 ± 10 ppt), benzene (20 ± 10 ppt), toluene (30 ± 20 ppt), C₈H₁₀ aromatics (23 ± 6 ppt) and C₉H₁₂ aromatics (36 ± 7 ppt). The MUMBA site was frequently influenced by VOCs of biogenic origin from a nearby strip of forested parkland to the east due to the dominant north-easterly afternoon sea breeze. VOCs from the more distant densely forested escarpment to the west also impacted the site, especially during two days of extreme heat and strong westerly winds. The relative amounts of different biogenic VOCs observed for these two biomes differed, with much larger increases of isoprene than of monoterpenes or methanol during the hot westerly winds from the escarpment than with cooler winds from the east. However, whether this was due to different vegetation types or was solely the result of the extreme temperatures is not entirely clear. We conclude that the clean marine air and biogenic signatures measured during the MUMBA campaign provide useful information about the typical abundance of several key VOCs and can be used to constrain chemical transport model simulations of the atmosphere in this poorly sampled region of the world. Full article

Both the global circulation model (GCM) and regional climate model (RCM) simulations suffer from model biases that eventually result in significant errors in regional forecasts. This model bias issue is addressed using the bias correction approach. This study examines the influence of bias correction on the performance of downscaling simulations of the East Asian winter climate using the Global/Regional Integrated Model system (GRIMs). To assess the bias correction approach, we conducted three sets of simulations for 25 winters (December to February) from 1982 to 2006 over East Asia. The GRIMs were forced by the (1) National Centers for Environmental Prediction (NCEP) Department of Energy (DOE) reanalysis data, (2) original NCEP Climate Forecast System (CFS) data, and (3) bias-corrected CFS data. The GCM climatological means were adjusted based on the NCEP–DOE reanalysis data. The bias correction method was applied to zonal and meridional wind, temperature, geopotential height, specific humidity, and sea surface temperature of the CFS data. The GCM-driven experiments with/without bias correction were compared with the reanalysis-driven simulation. The results of this comparison suggest that the application of bias correction improves the downscaled climate in terms of the climatological mean, inter-annual variability, and extreme events owing to the elimination of errors in large-scale circulations. The effect of bias correction on the simulated extreme event is not as significant as those on the climatological mean and inter-annual variability, but the increased skill appears to be a clue for potential use for predicting extreme events. Full article

Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary $P{M}_{10}$ fractions are complex and non-linear, environmental authorities need tools to assess their plans designed to improve the air quality as requested from environmental laws. Multi-criteria decision analysis (MCDA) can be applied to support decision makers, by processing quantitative opinions provided by pools of experts, especially when different views on social aspects should be considered. The results obtained through this approach, however, can be highly dependent on the subjectivity of experts. To partially overcome these challenges, this paper suggests a two-step methodology in which an MCDA is fed with the solution of a multi-objective analysis (MOA). The methodology has been applied to a test case in northern Italy and the results show that this approach is a viable solution for the inclusion of subjective criteria in decision making, while reducing the impact of uncertain expert opinions for data that can be computed through the MOA. Full article

This study aimed to determine indoor and outdoor levels of volatile organic compounds (VOCs) and to assess potential risks among residents living in the vicinity of an optoelectronics industrial park in 2006–2007. We used steel canisters to collect 72 indoor samples and 80 outdoor samples over 24 h. Gas chromatography with a mass-selective detector was used for qualitative and quantitative analyses. The amounts of time residents spent doing activities in different microenvironments were determined by the self-administered questionnaire. The chronic hazard index (HIc) and cancer risk were applied to assess the non-carcinogenic and carcinogenic risks of VOCs among residents. Four VOCs of ethanol (indoor: 77.8 ± 92.8 μg/m³; outdoor: 26.8 ± 49.6 μg/m³), toluene (67.0 ± 36.7 μg/m³; 56.9 ± 19.0 μg/m³), m/p-xylene (50.8 ± 66.1 μg/m³; 21.2 ± 20.3 μg/m³), and acetone (37.7 ± 27.5 μg/m³; 25.8 ± 9.8 μg/m³) were identified as dominant components in both the indoor and outdoor environments. Total VOCs and six VOCs of benzene, toluene, ethylbenzene, m/p-xylene, o-xylene, and ethanol in indoor sites were significantly higher than those in outdoor sites (all p-values < 0.05). All estimated HIc values were less than unity and the cancer risk of benzene exposure was 1.8 × 10⁻⁴ (range: 9.3 × 10⁻⁵ to 3.4 × 10⁻⁴) based on resident time-weighted patterns. Strategies to reduce benzene exposure should be implemented to protect public health. Full article

The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature ( $T_d$ ). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of $T_d$ in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and $T_d$ can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes. Full article