Local Humidity Research Articles

Impacts of urban air temperature and humidity on building cooling and heating energy demand in 15 cities of eastern China

Urban climates could significantly impact building energy consumption. This study aimed to investigate the impact of urban-rural disparities in temperature and humidity on building cooling and heating demand in multiple cities. Fixed stations were established using temperature/humidity loggers deployed at 17 pairs of urban and rural sites in 15 cities in eastern China. The study analyzed the differences in air temperature (ΔTa), relative humidity (ΔRH), and dew-point temperature (ΔTdew) between the urban and rural sites. These climatic data were then used as inputs for the energy simulation of a residential building. The following results were revealed: (1) ΔTa was consistently higher at night than during the day. In comparison with the rural reference sites, the RH values at all urban sites were lower; however, some urban sites displayed lower Tdew, while others exhibited higher Tdew. (2) Regarding annual total energy demands, urban buildings exhibited variable changes in energy components compared to rural buildings. Sensible cooling demands increased by 10 %–36 %, while heating demands decreased by 9 %–30 %. Latent cooling demands ranged from a decrease of 12 % to an increase of 17 %. As a result, overall changes in annual total energy demands (cooling + heating) were relatively small, ranging from −2 % to +7 %. (3) Regarding daily total energy demands, a 1 °C increase in ΔTa led to a 12.1 % increase in sensible cooling demand and an 8 % decrease in heating demand. At the same time, a 1 °C variation in ΔTdew corresponded to a 14.6 % change in latent cooling demand. (4) Regarding the daily peak load, modifications in local temperature and humidity in urban areas had a more pronounced impact on daily peak heating loads than on daily peak cooling loads. This study could enhance our understanding of how urban local climates affect building cooling and heating energy demands.

Quantifying climatic and socioeconomic drivers of urban malaria in Surat, India: a statistical spatiotemporal modelling study

Cities are becoming increasingly important habitats for mosquito vectors of disease. The pronounced heterogeneity of urban landscapes challenges our understanding of the effects of climate and socioeconomic factors on mosquito-borne disease dynamics at different spatiotemporal scales. Here, we quantify the impact of climatic and socioeconomic factors on urban malaria risk, using an extensive dataset in both space and time for reported Plasmodium falciparum cases in the city of Surat, northwest India. We analysed 10 years of monthly P falciparum cases resolved at three nested spatial resolutions (seven zones, 32 units, and 478 worker units) with a Bayesian hierarchical mixed model that incorporates the effects of population density, poverty, relative humidity, and temperature, in addition to random effects (structured and unstructured). To reduce dimensionality and avoid correlation of covariates, socioeconomic variables from survey data were summarised into main axes of variation using principal component analysis. With model selection, we identified the main drivers of spatiotemporal variation in malaria incidence rates at each of the three spatial resolutions. We also compared observations to model-fitted cases by quantifying the percentage of predictions within five discrete levels of malaria risk. The spatial variation of urban malaria cases was stationary over time, whereby locations with high and low yearly cases remained largely consistent across years. Local socioeconomic variation could be summarised with three principal components accounting for approximately 80% of the variance. The model that incorporated local temperature and relative humidity together with two of these principal components, largely representing population density and poverty, best explained monthly malaria patterns in models formulated at the three different spatial scales. As model resolution increased, the effect size of humidity decreased, whereas those of temperature and the principal component associated with population density increased. Model predictions accurately captured aggregated total monthly cases for the city; in space-time, they more closely matched observations at the intermediate scale, with around 57% of units estimated to fall in the observed category on average across years. The mean absolute error was lower at the intermediate level, showing that this is the best aggregation level to predict the space-time dynamics of malaria incidence rates across the city with the selected model. This statistical modelling framework provides a basis for development of a climate-driven early warning system for urban malaria for the units of Surat, including spatially explicit prediction of malaria risk several weeks to months in advance. Results indicate environmental and socioeconomic covariates for which further measurement at high resolution should lead to model improvement. Advanced warning combined with local surveillance and knowledge of disease hotspots within the city could inform targeted intervention as part of urban malaria elimination efforts. US National Institutes of Health.

Innovative dual-function system for efficient CO2 absorption and utilization: Local humidity swing fabric and microalgae-embedded hydrogel

In this study, we explored the use of local humidity swing (LHS) adsorption technology for carbon dioxide (CO2) capture from air, leveraging its low energy consumption and cost-effectiveness. By employing a coating technique, we immobilized ion exchange resin (IER) particles on fabrics with different hydrophilicities. The coating, consisting of silk fibroin (silk) and glycerol, formed a thin membrane on the fabric surface, effectively immobilizing the IER particles. The results revealed that hydrophobic polyester fabric with an initial silk concentration of 2 wt% (2 %SF/Gly@IER-PF) exhibited superior CO2 adsorption capacity (11.07 ml/g at 10 % relative humidity) and stability at varying humidities (10–90 %) compared to the hydrophilic cotton fabric. By covering the 2 %SF/Gly@IER-PF with a hydrophilic, highly water-absorbing non-woven fabric, one-way moisture transfer between the two types of fabrics was made, significantly affecting the water content and the release of adsorbed CO2 within the SF/Gly@IER-PF, and CO2 adsorption/desorption cycles could be achieved by detaching and attaching the water-absorbing fabric from the 2 %SF/Gly@IER-PF. The SF/Gly@IER-PF-based LHS system was combined with a silk/alginate composite hydrogel containing live microalgae, forming a dual-function CO2 fixation system. The functionalized fabric efficiently captured CO2 from the air, which was subsequently utilized by the gel-immobilized microalgae. As a result, the microalgae showed a higher proliferation rate compared to the control hydrogel system without the attachment of SF/Gly@IER-PF. This demonstrates the potential application of the dual-function system in effectively reducing CO2 levels from the air.

Analysis of Mould Exposure of Immunosuppressed Patients at a German University Hospital.

Moulds are ubiquitous components of outdoor and indoor air and local conditions, temperature, humidity and season can influence their concentration in the air. The impact of these factors on mould exposure in hospitals and the resulting risk of infection for low to moderately immunocompromised patients is unclear. In the present retrospective analysis for the years 2018 to 2022, the monthly determined mould contamination of the outdoor and indoor air at the University Hospital Frankfurt am Main is compared with the average air temperature and the relative humidity. Mould infections (Aspergillus spp., Mucorales) of low to moderately immunosuppressed patients of a haematological-oncological normal ward were determined clinically according to the criteria of the European Organisation for Research and Treatment of Cancer (EORTC, Brussels, Belgium) and of the National Reference Centre for Surveillance of Nosocomial Infections (NRC-NI, Berlin, Germany). The data revealed that in the summer months (May-October), increased mould contamination was detectable in the outdoor and indoor air compared to the winter months (November-April). The mould levels in the patient rooms followed the detection rates of the outdoor air. Two nosocomial Aspergillus infections, one nosocomial Mucorales (Rhizopus spp.) infection (according to both NRC-NI and EORTC criteria) and five Aspergillus spp. infections (according to EORTC criteria) occurred in 4299 treated patients (resulting in 41,500 patient days). In our study, the incidence density rate of contracting a nosocomial mould infection (n = 3) was approximately 0.07 per 1000 patient days and appears to be negligible.

Investigation of ionomer hydration and local relative humidity in platinum and non-noble based catalyst layers in proton exchange membrane fuel cells using SAXS

Although the proton exchange membrane fuel cell has been studied for many years, there is still no precise description of the internal operating conditions on a local scale, even though the concentration of water, or its content, in the components of the membrane-electrode assembly plays a major role in the transport of protons and gases, and therefore in performance and durability. In this work, small angle X-ray scattering operando measurements were performed on membrane-electrode assemblies containing different catalysts, and a data processing method was developed in order to extract the contribution of the ionomer, not only in the membrane, but also within the catalyst layers. Thus, the hydration of the ionomer within the membrane and the catalyst layers was quantified during the cell operation. Predictably, during current generation, water is produced, resulting in an increase in the amount of water in all components of the membrane-electrode assembly, and water concentration increases from anode to cathode. Crucially however, the employed method facilitates the determination of the current density at which saturation is reached within the catalyst layer.

The Global Patterns of Instantaneous CO2 Forcing at the Top of the Atmosphere and the Surface

Abstract The radiative forcing of carbon dioxide (CO2) at the top of the atmosphere (TOA) has a rich spatial structure and has implications for large-scale climate changes, such as poleward energy transport and tropical circulation change. Beyond the TOA, additional CO2 increases downwelling longwave at the surface, and this change in flux is the surface CO2 forcing. Here we thoroughly evaluate the spatiotemporal variation of the instantaneous, longwave CO2 radiative forcing at both the TOA and surface. The instantaneous forcing is calculated with a radiative transfer model using ERA5 reanalysis fields. Multivariate regression models show that the broadband forcing at the TOA and surface are well predicted by local temperatures, humidity, and cloud radiative effects. The difference between the TOA and surface forcing, the atmospheric forcing, can be either positive or negative and is mostly controlled by the column water vapor, with little explicit dependence on the surface temperature. The role of local variables on the TOA forcing is also assessed by partitioning the change in radiative flux to the component emitted by the surface versus that emitted by the atmosphere. In cold, dry regions, the surface and atmospheric contribution partially cancel out, leading to locally weak or even negative TOA forcing. In contrast, in the warm, moist regions, the surface and atmospheric components strengthen each other, resulting in overall larger TOA forcing. The relative contributions of surface and atmosphere to the TOA forcing depend on the optical thickness in the current climate, which in turn is controlled by the column water vapor.

The effect of weather conditions on scores at the United States Masters golf tournament.

This paper investigates the sensitivity of golfers' performance to meteorological conditions at the men's US Masters tournament over the 40-year period 1980-2019. The mean and standard deviation of round scores are related to local temperature, humidity, wind speed and direction, and concurrent and antecedent precipitation. Mean scores are more dependent on weather conditions than the variability of scores in a given round. The best predictor of mean scores is the wet-bulb temperature in rounds one and two, and the zonal wind speed in rounds three and four. Across both sets of rounds (1 and 2, and 3 and 4), the wet-bulb temperature is a better predictor of mean scores than the air temperature, which implies that atmospheric moisture content affects scores. In general, golfers take fewer shots and so perform better in warmer and calmer conditions. The synergestic effect of several weather variables explains over 44% of the variance in mean scores. Mean meteorological conditions during play are a much better predictor of the players' average performance than the standard deviation of the weather variables. The golfers' performance becomes more variable in cooler conditions with a wider range of scores. Precipitation during play and the dampness of the ground (as quantified by rainfall up to ten days before play) do not have a consistent and statistically significant effect on the competitors' performance. In short, this paper demonstrates that golf scores are dependent on weather conditions.

Understanding diarrhoeal diseases in response to climate variability and drought in Cape Town, South Africa: a mixed methods approach

BackgroundThe climate of southern Africa is expected to become hotter and drier with more frequent severe droughts and the incidence of diarrhoea to increase. From 2015 to 2018, Cape Town, South Africa, experienced a severe drought which resulted in extreme water conservation efforts. We aimed to gain a more holistic understanding of the relationship between diarrhoea in young children and climate variability in a system stressed by water scarcity.MethodsUsing a mixed-methods approach, we explored diarrhoeal disease incidence in children under 5 years between 2010 to 2019 in Cape Town, primarily in the public health system through routinely collected diarrhoeal incidence and weather station data. We developed a negative binomial regression model to understand the relationship between temperature, precipitation, and relative humidity on incidence of diarrhoea with dehydration. We conducted in-depth interviews with stakeholders in the fields of health, environment, and human development on perceptions around diarrhoea and health-related interventions both prior to and over the drought, and analysed them through the framework method.ResultsFrom diarrhoeal incidence data, the diarrhoea with dehydration incidence decreased over the decade studied, e.g. reduction of 64.7% in 2019 [95% confidence interval (CI): 5.5–7.2%] compared to 2010, with no increase during the severe drought period. Over the hot dry diarrhoeal season (November to May), the monthly diarrhoea with dehydration incidence increased by 7.4% (95% CI: 4.5–10.3%) per 1 °C increase in temperature and 2.6% (95% CI: 1.7–3.5%) per 1% increase in relative humidity in the unlagged model. Stakeholder interviews found that extensive and sustained diarrhoeal interventions were perceived to be responsible for the overall reduction in diarrhoeal incidence and mortality over the prior decade. During the drought, as diarrhoeal interventions were maintained, the expected increase in incidence in the public health sector did not occur.ConclusionsWe found that that diarrhoeal incidence has decreased over the last decade and that incidence is strongly influenced by local temperature and humidity, particularly over the hot dry season. While climate change and extreme weather events especially stress systems supporting vulnerable populations such as young children, maintaining strong and consistent public health interventions helps to reduce negative health impacts.

Water activity in subaerial microbial biofilms on stone monuments

Stone monuments can be difficult environments for life, particularly with respect to liquid water access. Nevertheless, microbial communities are found on them with apparent ubiquity. A variety of strategies for access to liquid water have been proposed. Regardless of their water-retention mechanisms details, though, we argue that water activity (a key indicator for cell viability) is constrained by environmental conditions, largely independently of community structure, and is predicted by the local temperature and relative humidity. However, direct measurement of water activity in SABs, particularly those growing on stone surfaces, is difficult. A method for estimating water activity within SABs is presented that uses a minimally invasive combination of conservative sampling, weather data, confocal imaging, and mathematical modeling. Applying the methodology to measurements from the marble roofs of the Federal Hall National Memorial and of the Thomas Jefferson Memorial, estimations are made for water activity in their subaerial stone communities over the course of an approximately one year period.

The genetic secrets of adaptation: decoding the significance of the 30-bp insertion in the KRT77 gene for Chinese cattle

The KRT77 gene is a type II epithelial cell α-keratin gene family member that plays a crucial role in animal epidermal and coat formation. This study aimed to investigate the relationship between the KRT77 gene and the adaptability of Chinese cattle in varying environments by exploring the distribution of an exon insertion of the KRT77 gene in different cattle populations. Our analysis involved amplifying and sequencing DNA samples from 362 individuals from 24 cattle breeds in China. Our findings reveal a gradual increase in the frequency of insertion from the northwest to the southeast population. We conducted an association analysis between the genotypes and climate data, revealing a correlation between the insertion and local annual mean temperature, relative humidity, and temperature humidity index. The study highlights the significance of the newly identified KRT77 gene insertion as a variation associated with environmental adaptation in Chinese cattle. This insertion variation increased insights into the genetic mechanisms that drive adaptation in Chinese cattle, emphasizing the importance of the 30-bp insertion in the KRT77 gene. Our findings facilitate further research to improve cattle breeding strategies for adaptability to changing environments from the northwest to the southeast population. In conclusion, this study provides value.

Local drying climate magnified by urbanization in West Africa

AbstractUrbanization often increases surface runoff and land surface temperature due to loss of land cover. However, the effect of urbanization on local atmospheric humidity remains understudied despite the disastrous effects it can have on human health and water‐food‐energy‐ecosystem nexus. Here, we examined changes in atmospheric humidity in the West Africa (WA) region between 1985 and 2018. There was an increase in vapour pressure and decrease in atmospheric humidity in urban areas suggesting intensified urban drying island (UDI) effects. Rapid urban expansion has aggravated UDI effect in recent years, particularly during the hot, wet summer but mild during the cold, and dry winter. In future climate, the impacts of the UDI effect in the region may be enormous considering the increasing rate of urbanization in the region. To achieve a sustainable future, city planners and policymakers should consider the UDI effect by promoting developments that increase green land cover. Overall, this study provides a detailed understanding of the urban ecosystem's environmental change, which is helpful for local climate change adaptation and mitigation.

Using drone soundings to study the impacts and compositions of plumes from a gigantic coal-fired power plant

The immense impacts of coal-fired power plant plumes on the atmospheric environment have caused great concern linked to climate and health issues. However, studies on the field observations of aerial plumes are relatively limited, mainly due to the lack of suitable plume observation tools and techniques. In this study, we use a multicopter unmanned aerial vehicle (UAV) sounding technique to study the influences of the aerial plumes of the world's fourth-largest coal-fired power plant on the atmospheric physical/chemical conditions and air quality. A set of species, including 106 volatile organic compounds (VOCs), CO, CO2, CH4, PM2.5, and O3, and meteorological variables of temperature (T), specific humidity (SH), and wind data, are collected by the UAV sounding technique. The results reveal that the large-scale plumes of the coal-fired power plant cause local temperature inversion and humidity changes, and even affect the dispersion of pollutants below. The chemical compositions of coal-fired power plant plumes are significantly different from those of another ubiquitous vehicular source. High fractions of ethane, ethene, and benzene and low fractions of n-butane and isopentane found in plumes could serve as the key features to help distinguish the influences of coal-fired power plant plumes from other pollution sources in a particular area. By taking the ratios of pollutants (e.g., PM2.5, CO, CH4, and VOCs) to CO2 in plumes and the CO2 emission amounts of the power plant into calculation, we enable the easy quantification of the specific pollutant emissions released from power plant plumes to the atmosphere. In summary, observation by using drone soundings dissecting the aerial plumes provides a new methodology that allows aerial plumes to be readily detected and characterized. Furthermore, the influences of the plumes on the atmospheric physical/chemical conditions and air quality can be assessed rather straightforwardly, which was not easily achievable in the past.

Numerical investigation of water and heat recovery from flue gas by using nanoporous ceramic membrane tubes

Direct emission of high humidity flue gas results in great wastage of water and thermal energy. Ceramic membrane technology has been widely regarded as a potential technology for water and heat recovery from flue gas. This study presents numerical investigations of water and heat recovery processes from flue gas by using nanoporous ceramic membrane tubes (CMTs). A comprehensive mathematical model is developed based on the Kelvin equation, and the Hagen–Poiseuille equation is applied to calculate the bilateral pressure difference needed for continuous recovery operation. Decreasing the pore size of the separation layer of the ceramic membrane improves the capillary condensation flux but also drastically increases the required bilateral pressure difference. CMT with a pore size of 20 nm is appreciated for the studied conditions. The performances of the CMTs located in the last rows along the flow direction are limited by local low gas temperature and humidity. Twelve rows of tubes are suggested to be arranged along the gas flow direction for ceramic membrane devices with pore sizes of 20 nm and higher. A low transverse spacing obviously improves the overall water and heat recovery efficiency of the device, decreases the performance of each tube, and enhances the gas flow resistance. A transverse spacing ratio of less than 1.4 is suitable for the studied conditions. A combined arrangement by substituting the tubes located in the last rows with those of smaller pore size is a better method than using uniform tubes. The device with combined 20 and 10 nm CMTs is suggested for the studied conditions.

A review of dairy cattle heat stress mitigation in Indonesia.

Indonesia is a tropical country with a hot climate. In tropical nations such as Indonesia, heat stress is a key reason for the reduced productivity of dairy cattle. Heat stress is a combination of internal and external stimuli that affects an animal, raises its body temperature, and causes it to react physiologically. Most Indonesian dairy cattle are Friesian Holstein (FH), imported from European nations with a temperate environment with low temperatures in the range of 5°C-25°C. Indonesia has a tropical climate with a high ambient temperature that can reach 34°C during the day and the local relative humidity varies between 70% and 90%. Temperature and humidity are two microenvironment factors that may impact the production and heat release in FH cattle. More than 98% of the entire dairy cattle population in Indonesia is found on Java Island. On Java Island, there are between 534.22 and 543.55 thousand heads of cattle, while the dairy cattle population outside Java Island is just 6.59 thousand heads of cattle. The milk output climbs by an average of 3.34% per year, or approximately 909.64 thousand tons and the average annual growth in whole milk consumption was 0.19 L/capita. Indonesian cow milk output has been unable to keep pace with the country's increasing demand. This study aimed to review the strategies to mitigate heat stress in FH dairy cattle in Indonesia.

To Develop an Application for Farmer's of Systematic Farming by using Machine Learning

The foundation of the social and economic development of our nation is agriculture. However, the bulk of farmers continue to struggle for access to better agricultural facilities. With the support of various government policies, the government also assists farmers with their benefits. The use of the internet and smartphones for smart farming is well known among today's farmers. Growing numbers of educated people are working in agriculture, and they have started using cell phones in rural areas. This Crop Guidance and Farmer's Friend application's primary goal is to help farmers increase their production while also keeping them informed about the most recent agricultural-based data utilised for smart farming. The suggested system is intended to monitor local weather factors like temperature, humidity, and environmental changes. Farmers' time and effort are reduced by this application, which also helps them obtain the current market price for various harvests, fertilisers, and vegetables without having to go to the market. Through this application, the data (value, climate, and most recent rural technology) will be sent to the farmers. This app offers farmers a lot of assistance and keeps them informed. It provides a means of support for practically the whole population, boosting national GDP and creating jobs

Passive evaporative coolers for postharvest storage of fruit and vegetables: Where to best deploy them and how well do they perform

Passive evaporative coolers have a huge potential to help smallholder farmers to preserve their fresh fruit and vegetables longer after harvest. However, we could benefit from more transparent information on where evaporative coolers perform sufficiently well to extend the postharvest life of the fresh produce significantly. Unsatisfactory evaporative cooler performance is a potential cause for farmers' limited adoption of this technology to reduce food losses. Our objective is to present easy-to-use tools that help to better scope regions with the best potential for direct passive evaporative coolers and for effectively deploying it. This information should help avoid installing evaporative coolers in areas with environmental conditions that only induce a temperature depression of a few degrees Celsius. Concretely, we developed design charts of the achievable temperature depression by evaporative cooling based on the local air temperature and humidity. We quantified for apple, banana, mango, and tomato the resulting additional days in postharvest life gained by storing the produce in an evaporative cooler. For these fruits, the gain in postharvest life using passive cooling is roughly 2–15 days for temperate climates with an ambient temperature of 20°C and a humidity of 50%. We present geographical maps of India, Nigeria, and the entire world at a 30 km resolution that answer how much evaporative cooling can maximally decrease the produce temperature and extend postharvest life for banana fruit. We found that passive evaporative cooling could induce up to a 7-day gain in postharvest life. We make these maps available online. We also quantify how well evaporative coolers perform concerning reducing the temperature and how they should be sized. Our results will facilitate installing evaporative coolers only in suitable regions. Our data also show in which months the cooler can be operated with the best performance. We thereby help avoid disillusion and loss of trust in the technology with smallholder farmers, policymakers, farmers, or farmer cooperatives. Further catalyzing the implementation of small-scale evaporative coolers can bring farmers significant gains in postharvest life, reduce food losses, and increase revenues.

Comparison between the Operational and Statistical Daily Maximum and Minimum Temperature Forecasts on the Central Coast of Peru

Abstract Multiple linear regression models were developed for 1–3-day lead forecasts of maximum and minimum temperature for two locations in the city of Lima, on the central coast of Peru (12°S), and contrasted with the operational forecasts issued by the National Meteorological and Hydrological Service—SENAMHI and the output of a regional numerical atmospheric model. We developed empirical models, fitted to data from the 2000–13 period, and verified their skill for the 2014–19 period. Since El Niño produces a strong low-frequency signal, the models focus on the high-frequency weather and subseasonal variability (60-day cutoff). The empirical models outperformed the operational forecasts and the numerical model. For instance, the high-frequency annual correlation coefficient and root-mean-square error (RMSE) for the 1-day lead forecasts were 0.37°–0.53° and 0.74°–1.76°C for the empirical model, respectively, but from around −0.05° to 0.24° and 0.88°–4.21°C in the operational case. Only three predictors were considered for the models, including persistence and large-scale atmospheric indices. Contrary to our belief, the model skill was lowest for the austral winter (June–August), when the extratropical influence is largest, suggesting an enhanced role of local effects. Including local specific humidity as a predictor for minimum temperature at the inland location substantially increased the skill and reduced its seasonality. There were cases in which both the operational and empirical forecast had similar strong errors and we suggest mesoscale circulations, such as the low-level cyclonic vortex over the ocean, as the culprit. Incorporating such information could be valuable for improving the forecasts. Significance Statement We wanted to compare the temperature of the operational forecast of the Meteorological and Hydrological Service, an atmospheric model, and persistence with the observed temperatures on the Peruvian central coast. In addition, we generated an empirical forecast model considering both atmospheric and local predictors. We got better results with this empirical model, considering the highest Pearson correlations and the lowest RMSE values. These results will allow us to use this empirical model as the main tool to automate the forecast on the central coast of Peru. Future work should be aimed at testing the skill of this model for forecasting in other cities of Peru.

Secondary aerosol formation drives atmospheric particulate matter pollution over megacities (Beijing and Seoul) in East Asia

Atmospheric particulate matter (PM) pollution in Beijing and Seoul is an urgent concern because of the dense population and the role of the capital city. This study aimed to understand haze formation over East Asia during winter by simultaneously measuring the in situ aerosol chemical composition in the two megacities. During the sampling period, a similar pollution situation characterized by extremely low SO2 (approximately 1 ppbv) and high NOx (approximately 20 ppbv) concentrations and secondary inorganic aerosol (SIA)-dominated PM was found in both cities. Nitrate dominated the inorganic components in the submicron particles in both cities and was more pronounced in Seoul than in Beijing. The enhanced SIA mass concentrations during pollution episodes were observed to be associated with an increased local atmospheric oxidation capacity (indicated by O3+NO2=Ox concentration) and ambient relative humidity under similar stagnant weather conditions. Regarding the thermodynamic equilibrium, abundant aerosol liquid water promoted the partitioning of gaseous HNO3 into its particle phase when pollution events occurred. This result emphasized the importance of local secondary aerosol formation for atmospheric PM pollution in East Asian megacities. The box model simulation of nitrate formation indicated that the homogeneous oxidation of NO2 by OH radicals was the major nitrate formation pathway in both megacities. The downward transport of nitrate from the residual layer also significantly contributed to nitrate concentrations. NOx and volatile organic compounds (VOCs) exhibited a non-linear relationship with nitrate formation. Reducing VOCs concentrations was an efficient approach to mitigate nitrate in both megacities. A reduction of more than 50% in NOx concentrations was required for the effective reduction of nitrate. This study highlighted that Beijing and Seoul were experiencing similar PM pollution situations, and nitrate reduction should be considered to improve their air quality.

Precipitable water vapor retrievals using a ground-based infrared sky camera in subtropical South America

Abstract. Atmospheric precipitable water vapor (PWV) is a critical quantity in fast-changing weather processes. Current retrieval techniques lack the spatial and/or temporal resolution necessary for a full PWV characterization. Here we investigate a retrieval method using an all-sky ground-based camera comprising a 14-bit 644 × 512-pixel microbolometer sensor array. The radiometrically calibrated infrared downwelling spectral radiance, Lλ, was acquired at rates of up to 3 min−1. For the studied site (23.56∘ S, 46.74∘W; 786 m a.s.l.) and spectral interval, Lλ is sensitive to the PWV; the vertical distribution of humidity; and their temporal, spatial, or seasonal variations. By comparing measured and simulated Lλ, we show that the PWV can be retrieved from prior knowledge of the local humidity profile. This information can originate from radiosonde data or statistical analysis of past vertical humidity distributions. Comparison with sun photometer PWV retrievals, for stable atmospheric conditions, showed an agreement of the average PWV within 2.8 % and a precision of subsequent retrievals of 1.9 %. The PWV was also retrieved as a bi-dimensional array, allowing for the investigation of spatial inhomogeneities of humidity distribution. The method can be used for daytime or nighttime retrievals, under partly cloudy sky conditions. Potential applications include studies on convection initiation processes.

Cholesteric Liquid Crystal Polymeric Coatings for Colorful Artificial Muscles and Motile Humidity Sensor Skin Integrated with Magnetic Composites.

Structural colorful cholesterics show impressive susceptibility to external stimulation, leading to applications in electro/mechano-chromic devices. However, out-of-plane actuation of structural colorful actuators based on cholesterics and the integration with other stimulation remains underdeveloped. Herein, colorful actuators and motile humidity sensors are developed using humidity-responsive cholesteric liquid crystal networks (CLCNs) and magnetic composites. The developed colorful actuator can exhibit synergistic out-of-plane shape morphing and color change in response to humidity, with CLCNs as colorful artificial muscles. Through the integration with magnetic control, the motile sensor can be navigated to open and confined spaces with the aid of friction to detect local relative humidity. The integration of multi-stimulation actuation of cholesteric magnetic actuators will expand the research frontier of structural colorful actuators and motile sensors for confined spaces.