The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorolog...The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.展开更多
In this study, the levels of meteorological parameters like maximum temperature (°F), relative temperature (°F), minimum temperature (°F), humidity (%), dew point (°F), wind speed (mph), rainfall (...In this study, the levels of meteorological parameters like maximum temperature (°F), relative temperature (°F), minimum temperature (°F), humidity (%), dew point (°F), wind speed (mph), rainfall (in), and air pressure (in) were analyzed for all three COVID-19 pandemic waves in the NCT of Delhi, India. After doing statistical analysis, the results showed that only a few parameters, like temperature (maximum, minimum, and relative), dew point, humidity, and air pressure, were linked to the start of COVID-19 pandemic waves, and rainfall had nothing to do with COVID-19 during any of the three waves. So, according to the results of this study, the Indian government should take strict steps to stop the spread of the fourth wave of COVID-19 and any other diseases that can spread in urban areas based on the meteorological conditions.展开更多
Accurate basic data are necessary to support performance-based design for achieving carbon peak and carbon neutral targets in the building sector.Meteorological parameters are the prerequisites of building thermal eng...Accurate basic data are necessary to support performance-based design for achieving carbon peak and carbon neutral targets in the building sector.Meteorological parameters are the prerequisites of building thermal engineering design,heating ventilation and air conditioning design,and energy consumption simulations.Focusing on the key issues such as low spatial coverage and the lack of daily or higher time resolution data,daily and hourly models of the surface meteorological data and solar radiation were established and evaluated.Surface meteorological data and solar radiation data were generated for 1019 cities and towns in China from 1988 to 2017.The data were carefully compared,and the accuracy was proved to be high.All the meteorological parameters can be assessed in the building sector via a sharing platform.Then,country-level meteorological parameters were developed for energy-efficient building assessment in China,based on actual meteorological data in the present study.This set of meteorological parameters may facilitate engineering applications as well as allowing the updating and expansion of relevant building energy efficiency standards.The study was supported by the National Science and Technology Major Project of China during the 13th Five-Year Plan Period,named Fundamental parameters on building energy efficiency in China,comprising of 15 top-ranking universities and institutions in China.展开更多
In this paper, we deployed the multiple linear regression method in developing a solar power output model for solar energy production, where the meteorological parameters are the independent variables. We fitted the m...In this paper, we deployed the multiple linear regression method in developing a solar power output model for solar energy production, where the meteorological parameters are the independent variables. We fitted the model and found that the meteorological variables considered accounted for 94.88% and 99.61% of the power output in both dry and rainy seasons. We observed from the work that the solar panel performs well in all seasons but slightly better in the rainy seasons. This could be attributed to the washing away of dust particles from solar panels by the rain and higher operating temperature different from the specified manufactured temperature of 25°C. We observed that other factors such as the cloud slightly affect the optimal performance of the system. Panels inclined at an angle of 5° (Tilt) and facing south azimuth performs optimally, periodic washing of the surface of solar panels enhances optimal performance.展开更多
Poisson's equation is solved numerically by two direct methods, viz. Block Cyclic Reduction (BCR) method and Fourier Method. Qualitative and quantitative comparison between the numerical solutions obtained by two ...Poisson's equation is solved numerically by two direct methods, viz. Block Cyclic Reduction (BCR) method and Fourier Method. Qualitative and quantitative comparison between the numerical solutions obtained by two methods indicates that BCR method is superior to Fourier method in terms of speed and accuracy. Therefore. BCR method is applied to solve (?)2(?)= ζ and (?)2X= D from observed vorticity and divergent values. Thereafter the rotational and divergent components of the horizontal monsoon wind in the lower troposphere are reconstructed and are com pared with the results obtained by Successive Over-Relaxation (SOR) method as this indirect method is generally in more use for obtaining the streamfunction ((?)) and velocity potential (X) fields in NWP models. It is found that the results of BCR method are more reliable than SOR method.展开更多
This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weat...This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.展开更多
Anthropogenic heat emissions(AHE)play an important role in modulating the atmospheric thermodynamic and kinetic properties within the urban planetary boundary layer,particularly in densely populated megacities like Be...Anthropogenic heat emissions(AHE)play an important role in modulating the atmospheric thermodynamic and kinetic properties within the urban planetary boundary layer,particularly in densely populated megacities like Beijing.In this study,we estimate the AHE by using a Large-scale Urban Consumption of energY(LUCY)model and further couple LUCY with a high-resolution regional chemical transport model to evaluate the impact of AHE on atmospheric environment in Beijing.In areas with high AHE,the 2-m temperature(T_(2))increased to varying degrees and showed distinct diurnal and seasonal variations with maxima in night and winter.The increase in 10-m wind speed(WS_(10))and planetary boundary layer height(PBLH)exhibited slight diurnal variations but showed significant seasonal variations.Further,the systematic continuous precipitation increased by 2.1 mm due to the increase in PBLH and water vapor in upper air.In contrast,the precipitation in local thermal convective showers increased little because of the limited water vapor.Meanwhile,the PM_(2.5) reduced in areas with high AHE because of the increase in WS_(10) and PBLH and continued to reduce as the pollution levels increased.In contrast,in areas where prevailing wind direction was opposite to that of thermal circulation caused by AHE,the WS_(10) reduced,leading to increased PM_(2.5).The changes of PM_(2.5) illustrated that a reasonable AHE scheme might be an effective means to improve the performance of PM_(2.5) simulation.Besides,high AHE aggravated the O_(3) pollution in urban areas due to the reduction in NO_(x).展开更多
The coronavirus disease 2019(COVID-19)pandemic has become a public health crisis and a global catastrophe for human societies.In the absence of a vaccine,non-pharmaceutical interventions have been implemented across t...The coronavirus disease 2019(COVID-19)pandemic has become a public health crisis and a global catastrophe for human societies.In the absence of a vaccine,non-pharmaceutical interventions have been implemented across the world to reduce COVID-19 transmission.Recently,several studies have articulated the influence of meteorological parameters on COVID-19 infections in several countries.The purpose of this study was to investigate the effect of lockdown measures and meteorological parameters on COVID-19 daily confirmed cases and deaths in Bangladesh.Different parameters,such as case fatality rate,recovery rate,number of polymerase chain reaction tests,and percentages of confirmed cases were calculated for data covering March to September 2020.The meteorological data include daily average temperature,humidity,and wind speed,and their effects on COVID-19 data were analyzed after 0,3,7,and 14 days.A linear regression analysis revealed that all the studied meteorological parameters were positively correlated with the daily new cases and deaths in Bangladesh,while the highest correlations were observed for the 14 days incubation period.These results provide useful implications for the healthcare authorities to contain the pandemic in Bangladesh and beyond.展开更多
Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic.In this study,we adopted a high-resolution Weather Res...Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic.In this study,we adopted a high-resolution Weather Research and Forecasting(WRF)model to simulate the meteorology at two Arctic stations(Barrow and Summit)in April 2019.Simulation results were also evaluated by using surface measurements and statistical parameters.In addition,weather charts during the studied time period were also used to assess the model performance.The results demonstrate that the WRF model is able to accurately capture the meteorological parameters for the two Arctic stations and the weather systems such as cyclones and anticyclones in the Arctic.Moreover,we found the model performance in predicting the surface pressure the best while the performance in predicting the wind the worst among these meteorological predictions.However,the wind predictions at these Arctic stations were found to be more accurate than those at urban stations in mid-latitude regions,due to the differences in land features and anthropogentic heat sources between these regions.In addition,a comparison of the simulation results showed that the prediction of meteorological conditions at Summit is superior to that at Barrow.Possible reasons for the deviations in temperature predictions between these two Arctic stations are uncertainties in the treatments of the sea ice and the cloud in the model.With respect to the wind,the deviations may source from the overestimation of the wind over the sea and at coastal stations.展开更多
he analysis of meteorological data obtained from the Installed Automatic Weather Station (AWS) at Jinnah Station (70. 24°S, 25. 45°E ). East Antarctica is presented. This paper describes the meteorological c...he analysis of meteorological data obtained from the Installed Automatic Weather Station (AWS) at Jinnah Station (70. 24°S, 25. 45°E ). East Antarctica is presented. This paper describes the meteorological conditions of Jinnah Station for the years of 1991 and 1993. Due to some technical problems the data could not be received continuously in the year 1992. The significant temperature difference is found between the warmest and the coldest months. Climate shows the moderating effect of ocean.Low pressure and strong wind are common which represents the location of the station lies in the circum-POlar low pressure belt. The prevailing wind direction for all over the year is ESE.展开更多
In the urban atmosphere of Bengaluru, various volatile organic compounds(VOCs), particularly Benzene,Toluene, Ethylbenzene, and Xylene(BTEX), have shown an increasing trend in concentration. The present research was c...In the urban atmosphere of Bengaluru, various volatile organic compounds(VOCs), particularly Benzene,Toluene, Ethylbenzene, and Xylene(BTEX), have shown an increasing trend in concentration. The present research was conducted during summer and monsoon seasons, focusing on Kadubeesanahalli, a high-traffic area within the Bengaluru Metropolitan City. Hourly sample data was collected using a BTEX analyzer(Model GC955-600) and subsequently transformed into daily, monthly, and seasonal values. The study revealed distinct patterns in benzene concentrations. Benzene levels were lowest during the early morning hours, specifically from 1:00 a.m.to 7:00 a.m.. Concentrations then increased from 7:00 a.m. to 9:00 a.m. and again from 4:00 p.m. to 11:00 p.m.,corresponding to the morning and evening peak traffic hours. However, between 10:00 a.m. and 4:00 p.m., the concentration decreased due to reduced traffic levels. These diurnal variations in benzene concentration are influenced by meteorological parameters. Comparing the two seasons, higher concentrations of Benzene, EthylBenzene, and MP-xylene were observed during the summer season. This increase is attributed to the elevated temperatures during summer, which promote the vaporization of BTEX compounds. Conversely, lower BTEX concentrations were recorded during the monsoon season due to the wet deposition process. The observed positive correlation(r > 0.5) among BTEX parameters strongly suggests a common source, most likely originating from vehicular emissions.展开更多
Arid regions are highly vulnerable and sensitive to drought. The crops cultivated in arid zones are at high risk due to the high evapotranspiration and water demands. This study analyzed the changes in seasonal and an...Arid regions are highly vulnerable and sensitive to drought. The crops cultivated in arid zones are at high risk due to the high evapotranspiration and water demands. This study analyzed the changes in seasonal and annual evapotranspiration（ET） during 1951–2016 at 50 meteorological stations located in the extremely arid, arid, and semi-arid zones of Pakistan using the Penman Monteith（PM） method. The results show that ET is highly sensitive and positively correlated to temperature, solar radiation, and wind speed whereas vapor pressure is negatively correlated to ET. The study also identifies the relationship of ET with the meteorological parameters in different climatic zones of Pakistan. The significant trend analysis of precipitation and temperature（maximum and minimum） are conducted at 95% confidence level to determine the behaviors of these parameters in the extremely arid, arid, and semi-arid zones. The mean annual precipitation and annual mean maximum temperature significantly increased by 0.828 mm/a and 0.014℃/a in the arid and extremely arid zones, respectively. The annual mean minimum temperature increased by 0.017℃/a in the extremely arid zone and 0.019℃/a in the arid zone, whereas a significant decrease of 0.007℃/a was observed in the semi-arid zone. This study provides probabilistic future scenarios that would be helpful for policy-makers, agriculturists to plan effective irrigation measures towards the sustainable development in Pakistan.展开更多
In this paper we have developed a data logging and monitoring system, we validated the system by comparing the result from it with the existing one and found that the system performs slightly better than the existing ...In this paper we have developed a data logging and monitoring system, we validated the system by comparing the result from it with the existing one and found that the system performs slightly better than the existing work in the same area. This implies that the data logger and monitoring system is good and can be used to monitor solar energy variables even at the comfort of our homes. We fitted a model to the generated data and found that the meteorological variables considered accounted for 99.88% of the power output in the rainy seasons while 0.12% of the variation was not explained due to other factors. Solar panels inclined at an angle of 5° (Tilt) and facing South Pole perform optimally.展开更多
This study characterizes the black carbon in Agra, India home to the Taj Mahal--and situated in the lndo-Gangetic basin. The mean black carbon concentration is 9.5 μg m-3 and, owing to excessive biomass/fossil fuel c...This study characterizes the black carbon in Agra, India home to the Taj Mahal--and situated in the lndo-Gangetic basin. The mean black carbon concentration is 9.5 μg m-3 and, owing to excessive biomass/fossil fuel combustion and automobile emissions, the concentration varies considerably. Seasonally, the black carbon mass concentration is highest in winter, probably due to the increased fossil fuel consumption for heating and cooking, apart from a low boundary layer. The nocturnal peak rises prominently in winter, when the use of domestic heating is excessive. Meanwhile, the concentration is lowest during the monsoon season because of the turbulent atmospheric conditions and the process of washout by precipitation. The ratio of black carbon to brown carbon is less than unity during the entire study period, except in winter （December）. This may be because that biomass combustion and diesel exhaust are major black carbon contributors in this region, while a higher ratio in winter may be due to the increased consumption of fossil fuel and wood for heating purposes. ANOVA reveals significant monthly variation in the concentration of black carbon; plus, it is negatively correlated with wind speed and temperature. A high black carbon mass concentration is observed at moderate （1-2 m s-1） wind speed, as compared to calm or turbulent atmospheric conditions.展开更多
To estimate the monthly averaged solar radiations (global, diffuse and direct solar radiation) on horizontal surface and tilted surface over 10 stations (districts) in Bangladesh, thirty years monthly averaged data of...To estimate the monthly averaged solar radiations (global, diffuse and direct solar radiation) on horizontal surface and tilted surface over 10 stations (districts) in Bangladesh, thirty years monthly averaged data of various meteorological parameters namely the monthly averaged value of maximum temperature, minimum temperature, humidity and sunshine hours were used in this study. Assessment of the solar resources for the solar based renewable energy technologies of Bangladesh may be based upon this kind of measured data analyzed study. This study tried to estimate the monthly averaged solar radiation by presenting data in table and graph and finally analyze through equations and descriptions. Correlation between the measurements of monthly averaged solar radiation and the meteorological parameters was given for the selected 10 stations in Bangladesh. In conclusion, we tried to make a comparison among solar radiation on horizontal surface, fixed 20.83<sup> ° </sup> (degree) optimal tilt angle and variable optimal tilt surface at Dhaka station.展开更多
This study investigated the effects of gaseous emissions from crude storage tank and gas flaring on air and rainwater quality in Bonny Industrial Island. Ambient air quality parameters, rainwater and weather parameter...This study investigated the effects of gaseous emissions from crude storage tank and gas flaring on air and rainwater quality in Bonny Industrial Island. Ambient air quality parameters, rainwater and weather parameters were collected at 60 m, 80 m, 100 m, 200 m and control plot for 4 weeks at the Bonny. Rainwater parameters were investigated using standard laboratory tests. Data analyses were done using Analysis of variance, pairwise t-test and Pearson’s correlation statistical tools. Results show that emission rates, volatile organic compound (VOC) noise and flare temperature decreased with increasing distance from flare points and crude oil storage tanks. Findings further revealed the emission rates varied significantly with distance away from the gas flaring point (F = 6.196;p = 0.004). The mean concentration of pollutants between gas flare site and crude oil storage tank showed that CO (0.02 ± 0.001 - 0.002 ±0.001), SPM (0.011 ± 0.001 - 0.01 ± 0.001), VOC (0.005 ± 0.001 - 0.01 ± 0.001) and NO<sub>2</sub> (0.04 ± 0.001 - 0.005 ± 0.000) had significant variations (p > 0.05) with CO, O<sub>3</sub> and NO<sub>2</sub> having higher concentrations at the gas flare site while SPM, and VOC were higher around the crude oil storage tank site. Wind turbulence was higher around the gas flaring point (4.93 TKE) than the crude oil storage tank (4.55 TKE). Similarly, there was significant variation in the sun radiation, precipitation, and wind speed caused by gas flaring (1582.25 w/m<sup>2</sup>, 436.25 mm, 0.53 m/s) and crude oil storage tank (1536.25 w/m<sup>2</sup>, 3.91.41 mm, 0.51 m/s). There were also significant variations in flared temperature (F = 22.144;p = 0.001);NO<sub>2</sub> (F = 8.250;p = 0.001), CO (F = 6.000;p = 0.004) and VOC (F = 5.574;p = 0.006) with distance from the gas flaring point. The variation in the rainwater parameters with distance from the gas flaring indicated significant variations in pH (F = 5.594;p = 0.006). The study showed that the concentration of VOC and particulates were high in the supposedly control area which is perceived to be safe for human habitation. Significant variations exist in emission rate (p = 0.015), flare temperature (p = 0.001), NO<sub>2</sub> (p = 0.003), VOC (p = 0.001), noise (p = 0.041), hydrogen carbonate (p = 0.037) and chromium (p = 0.032) between the gas flaring and crude oil storage tank. Regular monitoring is advocated to mitigate the harmful effects of the pollutants.展开更多
Gamma radiation measurements integrated between 200 keV and 10.0 MeV were performed between 03/07/2017 and 05/24/2017 from a tower of 25 meters of altitude in the region of S^o Jos6 dos Campos, SP, Brazil. Throughout ...Gamma radiation measurements integrated between 200 keV and 10.0 MeV were performed between 03/07/2017 and 05/24/2017 from a tower of 25 meters of altitude in the region of S^o Jos6 dos Campos, SP, Brazil. Throughout this period, there were 9 intense and moderate rains with 11 arrivals of cold fronts coming from southern Brazil. Through measurements of gamma radiation integrated in the energy range mentioned above, the presence of these meteorological parameters and their variations in the region can clearly be observed. Through a potential calibration between the measured gamma radiation intensity and the observed rainfall intensity, it is possible to monitor rains by time interval using this gamma ray detector. Another very important parameter for the region consists of monitoring the number of passages of cold fronts that interfere in the local climatology. This low-cost, easy-to-operate technique can be applied and used in any tropical and equatorial region of the earth＇s surface.展开更多
Studies in various regions of the world have revealed that air pollution can have a significant influence on local climate. This study therefore considers the impact of concentration levels of atmospheric pollutants o...Studies in various regions of the world have revealed that air pollution can have a significant influence on local climate. This study therefore considers the impact of concentration levels of atmospheric pollutants on local climate of Delta state, Nigeria. Monthly and annual averaging of the daily pollutant concentrations and meteorological parameters within the period of investigation was carried out. Descriptive Statistics, correlation analysis, coefficient of determination (R<sup>2</sup>) analysis and least squares regression analysis of the selected meteorological parameters with CH<sub>4</sub> and O<sub>3</sub> concentrations for the period of 2003 to 2012 and NO<sub>2</sub> and CO<sub>2</sub> concentrations for the period of 2011 to 2014 were carried out. The regression relationship was then used to obtain predicted values for the meteorological parameters within the period of investigation. The results of the descriptive statistics of annual averages of CH<sub>4</sub>, O<sub>3</sub>, NO<sub>2</sub> and CO<sub>2</sub> concentrations within the period of investigation revealed that the emission levels breached FEPA and EGASPIN limits. The results of the correlation analysis indicated that CO<sub>2</sub> had a strong significant positive correlation with temperature with a correlation coefficient of 0.962, while a moderate negative correlation coefficient of 0.549 was obtained for CH<sub>4</sub>, and very weak correlation coefficients of -0.167 and 0.077 were obtained for O<sub>3</sub> and NO<sub>2</sub> respectively. CH<sub>4</sub>, O<sub>3</sub> and CO<sub>2</sub> had a moderately significant positive correlation with solar radiation with correlation coefficients of 0.661, 0.571 and 0.656 respectively, while a weak negative correlation coefficient of 0.106 was obtained for NO<sub>2</sub>. CH<sub>4</sub> had a strong significant positive correlation with relative humidity with a correlation coefficient of 0.859, while moderate correlation coefficients of -0.516 and 0.646 were obtained for NO<sub>2</sub> and CO<sub>2</sub> respectively, and a weak correlation coefficient of 0.345 was obtained for O<sub>3</sub>. CO<sub>2</sub> and CH<sub>4</sub> had a strong significant correlation with wind speed with correlation coefficients of 0.951 and -0.906 respectively, while a moderate negative correlation coefficient of 0.518 was obtained for O<sub>3</sub>, and a weak negative correlation coefficient of 0.317 was obtained for NO<sub>2</sub>. The predicted values of the meteorological parameters showed a significant level of agreement with their measured values. Therefore, among the atmospheric pollutants postulated as influencing meteorological parameters, CO<sub>2</sub> appears to be the most strongly significant in explaining temperature variations in this region of Niger Delta, with correlation coefficient of 96.2% and coefficient of determination (R<sup>2</sup>) of 0.926, implying that CO<sub>2</sub> influenced 92.6% variation in temperature in this part of Niger Delta within the period of investigation.展开更多
Vehicular emissions are considered one of the major anthropogenic sources of greenhouse gases and poor air quality in metropolitan cities.This study aims to see the correlation of CO_(2),CH_(4),and CO through monitori...Vehicular emissions are considered one of the major anthropogenic sources of greenhouse gases and poor air quality in metropolitan cities.This study aims to see the correlation of CO_(2),CH_(4),and CO through monitoring over a period from December 2020 to October 2021 covering three seasons’winter,summer,and monsoon at two different traffic locations of Delhi having different traffic volumes,road patterns,and traffic management.The annual average morning concentration of CO_(2),CH_(4)and CO was found(533±105),(7.3±3.1),(10.7±3.0)ppm at Najafgarh and(480±70),(5.2±1.8),(7.8±2.8)ppm at Rajendra Place,respectively.A relationship between concentration of all three gases and meteorological parameters such as temperature,humidity,wind speed and wind direction has also been investigated using Pearson correlation coefficient and pollution rose diagram.A comparable pattern in concentration was observed for all three gases in spatial(location)and temporal(diurnal)distribution.The concentration trend of CO_(2)in different seasons is winter>summer>monsoon,while in the case of CH_(4)winter=summer>monsoon but not any seasonal trend was noted in CO case.It is observed that CO_(2)has a good relation with CO(a tracer for vehicular emission)in terms of diurnal variation,whereas,CH_(4)does not represent a relation with CO and CO_(2)diurnally,suggesting that vehicles are the source of CO_(2)but not much contributing to other greenhouse gases like CH_(4).展开更多
Dry deposition velocity of total suspended particles （TSP） is an effective parameter that describes the speed of atmospheric particulate matter deposit to the natural surface. It is also an important indicator to th...Dry deposition velocity of total suspended particles （TSP） is an effective parameter that describes the speed of atmospheric particulate matter deposit to the natural surface. It is also an important indicator to the capacity of atmosphere self-depuration. However, the spatial and temporal variations in dry deposition velocity of TSP at different urban landscapes and the relationship between dry deposition velocity and the meteorological parameters are subject to large uncertainties. We concurrently investigated this relationship at four different landscapes of Guangzhou, from October to December of 2009. The result of the average dry deposition velocity is （1.49 ± 0.77）, （1.44 ± 0.77）, （1.13 ±0.53） and （1.82± 0.82） cm/sec for urban commercial landscape, urban forest landscape, urban residential landscape and country landscape, respectively. This spatial variation can be explained by the difference of both particle size composition of TSP and meteorological parameters of sampling sites. Dry deposition velocity of TSP has a positive correlation with wind speed, and a negative correlation with temperature and relative humidity. Wind speed is the strongest factor that affects the magnitude of TSP dry deposition velocity, and the temperature is another considerable strong meteorological factor. We also find out that the relative humidity brings less impact, especially during the dry season. It is thus implied that the current global warming and urban heat island effect may lead to correlative changes in TSP dry deposition velocity, especially in the urban areas.展开更多
文摘The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.
文摘In this study, the levels of meteorological parameters like maximum temperature (°F), relative temperature (°F), minimum temperature (°F), humidity (%), dew point (°F), wind speed (mph), rainfall (in), and air pressure (in) were analyzed for all three COVID-19 pandemic waves in the NCT of Delhi, India. After doing statistical analysis, the results showed that only a few parameters, like temperature (maximum, minimum, and relative), dew point, humidity, and air pressure, were linked to the start of COVID-19 pandemic waves, and rainfall had nothing to do with COVID-19 during any of the three waves. So, according to the results of this study, the Indian government should take strict steps to stop the spread of the fourth wave of COVID-19 and any other diseases that can spread in urban areas based on the meteorological conditions.
基金Project(2018YFC0704500)supported by the National Science and Technology Major Project of China during the 13th Five-Year Plan Period。
文摘Accurate basic data are necessary to support performance-based design for achieving carbon peak and carbon neutral targets in the building sector.Meteorological parameters are the prerequisites of building thermal engineering design,heating ventilation and air conditioning design,and energy consumption simulations.Focusing on the key issues such as low spatial coverage and the lack of daily or higher time resolution data,daily and hourly models of the surface meteorological data and solar radiation were established and evaluated.Surface meteorological data and solar radiation data were generated for 1019 cities and towns in China from 1988 to 2017.The data were carefully compared,and the accuracy was proved to be high.All the meteorological parameters can be assessed in the building sector via a sharing platform.Then,country-level meteorological parameters were developed for energy-efficient building assessment in China,based on actual meteorological data in the present study.This set of meteorological parameters may facilitate engineering applications as well as allowing the updating and expansion of relevant building energy efficiency standards.The study was supported by the National Science and Technology Major Project of China during the 13th Five-Year Plan Period,named Fundamental parameters on building energy efficiency in China,comprising of 15 top-ranking universities and institutions in China.
文摘In this paper, we deployed the multiple linear regression method in developing a solar power output model for solar energy production, where the meteorological parameters are the independent variables. We fitted the model and found that the meteorological variables considered accounted for 94.88% and 99.61% of the power output in both dry and rainy seasons. We observed from the work that the solar panel performs well in all seasons but slightly better in the rainy seasons. This could be attributed to the washing away of dust particles from solar panels by the rain and higher operating temperature different from the specified manufactured temperature of 25°C. We observed that other factors such as the cloud slightly affect the optimal performance of the system. Panels inclined at an angle of 5° (Tilt) and facing south azimuth performs optimally, periodic washing of the surface of solar panels enhances optimal performance.
文摘Poisson's equation is solved numerically by two direct methods, viz. Block Cyclic Reduction (BCR) method and Fourier Method. Qualitative and quantitative comparison between the numerical solutions obtained by two methods indicates that BCR method is superior to Fourier method in terms of speed and accuracy. Therefore. BCR method is applied to solve (?)2(?)= ζ and (?)2X= D from observed vorticity and divergent values. Thereafter the rotational and divergent components of the horizontal monsoon wind in the lower troposphere are reconstructed and are com pared with the results obtained by Successive Over-Relaxation (SOR) method as this indirect method is generally in more use for obtaining the streamfunction ((?)) and velocity potential (X) fields in NWP models. It is found that the results of BCR method are more reliable than SOR method.
文摘This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.
基金This work was supported in part by the National Key R&D Program of China(Grant No.2018YFC0213502)the National Natural Science Foundation of China(Grant No.41907190)the Beijing Municipal Commission of Science and Technology(No.Z19110000119004).
文摘Anthropogenic heat emissions(AHE)play an important role in modulating the atmospheric thermodynamic and kinetic properties within the urban planetary boundary layer,particularly in densely populated megacities like Beijing.In this study,we estimate the AHE by using a Large-scale Urban Consumption of energY(LUCY)model and further couple LUCY with a high-resolution regional chemical transport model to evaluate the impact of AHE on atmospheric environment in Beijing.In areas with high AHE,the 2-m temperature(T_(2))increased to varying degrees and showed distinct diurnal and seasonal variations with maxima in night and winter.The increase in 10-m wind speed(WS_(10))and planetary boundary layer height(PBLH)exhibited slight diurnal variations but showed significant seasonal variations.Further,the systematic continuous precipitation increased by 2.1 mm due to the increase in PBLH and water vapor in upper air.In contrast,the precipitation in local thermal convective showers increased little because of the limited water vapor.Meanwhile,the PM_(2.5) reduced in areas with high AHE because of the increase in WS_(10) and PBLH and continued to reduce as the pollution levels increased.In contrast,in areas where prevailing wind direction was opposite to that of thermal circulation caused by AHE,the WS_(10) reduced,leading to increased PM_(2.5).The changes of PM_(2.5) illustrated that a reasonable AHE scheme might be an effective means to improve the performance of PM_(2.5) simulation.Besides,high AHE aggravated the O_(3) pollution in urban areas due to the reduction in NO_(x).
文摘The coronavirus disease 2019(COVID-19)pandemic has become a public health crisis and a global catastrophe for human societies.In the absence of a vaccine,non-pharmaceutical interventions have been implemented across the world to reduce COVID-19 transmission.Recently,several studies have articulated the influence of meteorological parameters on COVID-19 infections in several countries.The purpose of this study was to investigate the effect of lockdown measures and meteorological parameters on COVID-19 daily confirmed cases and deaths in Bangladesh.Different parameters,such as case fatality rate,recovery rate,number of polymerase chain reaction tests,and percentages of confirmed cases were calculated for data covering March to September 2020.The meteorological data include daily average temperature,humidity,and wind speed,and their effects on COVID-19 data were analyzed after 0,3,7,and 14 days.A linear regression analysis revealed that all the studied meteorological parameters were positively correlated with the daily new cases and deaths in Bangladesh,while the highest correlations were observed for the 14 days incubation period.These results provide useful implications for the healthcare authorities to contain the pandemic in Bangladesh and beyond.
基金funded by the National Key Research and Development Program of China(Grant no.2022YFC3701204)the 2023 Outstanding Young Backbone Teacher of Jiangsu“Qinglan”Project(Grant no.R2023Q02)the National Natural Science Foundation of China(Grant no.41705103).
文摘Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic.In this study,we adopted a high-resolution Weather Research and Forecasting(WRF)model to simulate the meteorology at two Arctic stations(Barrow and Summit)in April 2019.Simulation results were also evaluated by using surface measurements and statistical parameters.In addition,weather charts during the studied time period were also used to assess the model performance.The results demonstrate that the WRF model is able to accurately capture the meteorological parameters for the two Arctic stations and the weather systems such as cyclones and anticyclones in the Arctic.Moreover,we found the model performance in predicting the surface pressure the best while the performance in predicting the wind the worst among these meteorological predictions.However,the wind predictions at these Arctic stations were found to be more accurate than those at urban stations in mid-latitude regions,due to the differences in land features and anthropogentic heat sources between these regions.In addition,a comparison of the simulation results showed that the prediction of meteorological conditions at Summit is superior to that at Barrow.Possible reasons for the deviations in temperature predictions between these two Arctic stations are uncertainties in the treatments of the sea ice and the cloud in the model.With respect to the wind,the deviations may source from the overestimation of the wind over the sea and at coastal stations.
文摘he analysis of meteorological data obtained from the Installed Automatic Weather Station (AWS) at Jinnah Station (70. 24°S, 25. 45°E ). East Antarctica is presented. This paper describes the meteorological conditions of Jinnah Station for the years of 1991 and 1993. Due to some technical problems the data could not be received continuously in the year 1992. The significant temperature difference is found between the warmest and the coldest months. Climate shows the moderating effect of ocean.Low pressure and strong wind are common which represents the location of the station lies in the circum-POlar low pressure belt. The prevailing wind direction for all over the year is ESE.
文摘In the urban atmosphere of Bengaluru, various volatile organic compounds(VOCs), particularly Benzene,Toluene, Ethylbenzene, and Xylene(BTEX), have shown an increasing trend in concentration. The present research was conducted during summer and monsoon seasons, focusing on Kadubeesanahalli, a high-traffic area within the Bengaluru Metropolitan City. Hourly sample data was collected using a BTEX analyzer(Model GC955-600) and subsequently transformed into daily, monthly, and seasonal values. The study revealed distinct patterns in benzene concentrations. Benzene levels were lowest during the early morning hours, specifically from 1:00 a.m.to 7:00 a.m.. Concentrations then increased from 7:00 a.m. to 9:00 a.m. and again from 4:00 p.m. to 11:00 p.m.,corresponding to the morning and evening peak traffic hours. However, between 10:00 a.m. and 4:00 p.m., the concentration decreased due to reduced traffic levels. These diurnal variations in benzene concentration are influenced by meteorological parameters. Comparing the two seasons, higher concentrations of Benzene, EthylBenzene, and MP-xylene were observed during the summer season. This increase is attributed to the elevated temperatures during summer, which promote the vaporization of BTEX compounds. Conversely, lower BTEX concentrations were recorded during the monsoon season due to the wet deposition process. The observed positive correlation(r > 0.5) among BTEX parameters strongly suggests a common source, most likely originating from vehicular emissions.
文摘Arid regions are highly vulnerable and sensitive to drought. The crops cultivated in arid zones are at high risk due to the high evapotranspiration and water demands. This study analyzed the changes in seasonal and annual evapotranspiration（ET） during 1951–2016 at 50 meteorological stations located in the extremely arid, arid, and semi-arid zones of Pakistan using the Penman Monteith（PM） method. The results show that ET is highly sensitive and positively correlated to temperature, solar radiation, and wind speed whereas vapor pressure is negatively correlated to ET. The study also identifies the relationship of ET with the meteorological parameters in different climatic zones of Pakistan. The significant trend analysis of precipitation and temperature（maximum and minimum） are conducted at 95% confidence level to determine the behaviors of these parameters in the extremely arid, arid, and semi-arid zones. The mean annual precipitation and annual mean maximum temperature significantly increased by 0.828 mm/a and 0.014℃/a in the arid and extremely arid zones, respectively. The annual mean minimum temperature increased by 0.017℃/a in the extremely arid zone and 0.019℃/a in the arid zone, whereas a significant decrease of 0.007℃/a was observed in the semi-arid zone. This study provides probabilistic future scenarios that would be helpful for policy-makers, agriculturists to plan effective irrigation measures towards the sustainable development in Pakistan.
文摘In this paper we have developed a data logging and monitoring system, we validated the system by comparing the result from it with the existing one and found that the system performs slightly better than the existing work in the same area. This implies that the data logger and monitoring system is good and can be used to monitor solar energy variables even at the comfort of our homes. We fitted a model to the generated data and found that the meteorological variables considered accounted for 99.88% of the power output in the rainy seasons while 0.12% of the variation was not explained due to other factors. Solar panels inclined at an angle of 5° (Tilt) and facing South Pole perform optimally.
基金a part of the Aerosol Radiative Forcing over India project of the Indian Space Research Organization’s Geosphere Biosphere Programme
文摘This study characterizes the black carbon in Agra, India home to the Taj Mahal--and situated in the lndo-Gangetic basin. The mean black carbon concentration is 9.5 μg m-3 and, owing to excessive biomass/fossil fuel combustion and automobile emissions, the concentration varies considerably. Seasonally, the black carbon mass concentration is highest in winter, probably due to the increased fossil fuel consumption for heating and cooking, apart from a low boundary layer. The nocturnal peak rises prominently in winter, when the use of domestic heating is excessive. Meanwhile, the concentration is lowest during the monsoon season because of the turbulent atmospheric conditions and the process of washout by precipitation. The ratio of black carbon to brown carbon is less than unity during the entire study period, except in winter （December）. This may be because that biomass combustion and diesel exhaust are major black carbon contributors in this region, while a higher ratio in winter may be due to the increased consumption of fossil fuel and wood for heating purposes. ANOVA reveals significant monthly variation in the concentration of black carbon; plus, it is negatively correlated with wind speed and temperature. A high black carbon mass concentration is observed at moderate （1-2 m s-1） wind speed, as compared to calm or turbulent atmospheric conditions.
文摘To estimate the monthly averaged solar radiations (global, diffuse and direct solar radiation) on horizontal surface and tilted surface over 10 stations (districts) in Bangladesh, thirty years monthly averaged data of various meteorological parameters namely the monthly averaged value of maximum temperature, minimum temperature, humidity and sunshine hours were used in this study. Assessment of the solar resources for the solar based renewable energy technologies of Bangladesh may be based upon this kind of measured data analyzed study. This study tried to estimate the monthly averaged solar radiation by presenting data in table and graph and finally analyze through equations and descriptions. Correlation between the measurements of monthly averaged solar radiation and the meteorological parameters was given for the selected 10 stations in Bangladesh. In conclusion, we tried to make a comparison among solar radiation on horizontal surface, fixed 20.83<sup> ° </sup> (degree) optimal tilt angle and variable optimal tilt surface at Dhaka station.
文摘This study investigated the effects of gaseous emissions from crude storage tank and gas flaring on air and rainwater quality in Bonny Industrial Island. Ambient air quality parameters, rainwater and weather parameters were collected at 60 m, 80 m, 100 m, 200 m and control plot for 4 weeks at the Bonny. Rainwater parameters were investigated using standard laboratory tests. Data analyses were done using Analysis of variance, pairwise t-test and Pearson’s correlation statistical tools. Results show that emission rates, volatile organic compound (VOC) noise and flare temperature decreased with increasing distance from flare points and crude oil storage tanks. Findings further revealed the emission rates varied significantly with distance away from the gas flaring point (F = 6.196;p = 0.004). The mean concentration of pollutants between gas flare site and crude oil storage tank showed that CO (0.02 ± 0.001 - 0.002 ±0.001), SPM (0.011 ± 0.001 - 0.01 ± 0.001), VOC (0.005 ± 0.001 - 0.01 ± 0.001) and NO<sub>2</sub> (0.04 ± 0.001 - 0.005 ± 0.000) had significant variations (p > 0.05) with CO, O<sub>3</sub> and NO<sub>2</sub> having higher concentrations at the gas flare site while SPM, and VOC were higher around the crude oil storage tank site. Wind turbulence was higher around the gas flaring point (4.93 TKE) than the crude oil storage tank (4.55 TKE). Similarly, there was significant variation in the sun radiation, precipitation, and wind speed caused by gas flaring (1582.25 w/m<sup>2</sup>, 436.25 mm, 0.53 m/s) and crude oil storage tank (1536.25 w/m<sup>2</sup>, 3.91.41 mm, 0.51 m/s). There were also significant variations in flared temperature (F = 22.144;p = 0.001);NO<sub>2</sub> (F = 8.250;p = 0.001), CO (F = 6.000;p = 0.004) and VOC (F = 5.574;p = 0.006) with distance from the gas flaring point. The variation in the rainwater parameters with distance from the gas flaring indicated significant variations in pH (F = 5.594;p = 0.006). The study showed that the concentration of VOC and particulates were high in the supposedly control area which is perceived to be safe for human habitation. Significant variations exist in emission rate (p = 0.015), flare temperature (p = 0.001), NO<sub>2</sub> (p = 0.003), VOC (p = 0.001), noise (p = 0.041), hydrogen carbonate (p = 0.037) and chromium (p = 0.032) between the gas flaring and crude oil storage tank. Regular monitoring is advocated to mitigate the harmful effects of the pollutants.
文摘Gamma radiation measurements integrated between 200 keV and 10.0 MeV were performed between 03/07/2017 and 05/24/2017 from a tower of 25 meters of altitude in the region of S^o Jos6 dos Campos, SP, Brazil. Throughout this period, there were 9 intense and moderate rains with 11 arrivals of cold fronts coming from southern Brazil. Through measurements of gamma radiation integrated in the energy range mentioned above, the presence of these meteorological parameters and their variations in the region can clearly be observed. Through a potential calibration between the measured gamma radiation intensity and the observed rainfall intensity, it is possible to monitor rains by time interval using this gamma ray detector. Another very important parameter for the region consists of monitoring the number of passages of cold fronts that interfere in the local climatology. This low-cost, easy-to-operate technique can be applied and used in any tropical and equatorial region of the earth＇s surface.
文摘Studies in various regions of the world have revealed that air pollution can have a significant influence on local climate. This study therefore considers the impact of concentration levels of atmospheric pollutants on local climate of Delta state, Nigeria. Monthly and annual averaging of the daily pollutant concentrations and meteorological parameters within the period of investigation was carried out. Descriptive Statistics, correlation analysis, coefficient of determination (R<sup>2</sup>) analysis and least squares regression analysis of the selected meteorological parameters with CH<sub>4</sub> and O<sub>3</sub> concentrations for the period of 2003 to 2012 and NO<sub>2</sub> and CO<sub>2</sub> concentrations for the period of 2011 to 2014 were carried out. The regression relationship was then used to obtain predicted values for the meteorological parameters within the period of investigation. The results of the descriptive statistics of annual averages of CH<sub>4</sub>, O<sub>3</sub>, NO<sub>2</sub> and CO<sub>2</sub> concentrations within the period of investigation revealed that the emission levels breached FEPA and EGASPIN limits. The results of the correlation analysis indicated that CO<sub>2</sub> had a strong significant positive correlation with temperature with a correlation coefficient of 0.962, while a moderate negative correlation coefficient of 0.549 was obtained for CH<sub>4</sub>, and very weak correlation coefficients of -0.167 and 0.077 were obtained for O<sub>3</sub> and NO<sub>2</sub> respectively. CH<sub>4</sub>, O<sub>3</sub> and CO<sub>2</sub> had a moderately significant positive correlation with solar radiation with correlation coefficients of 0.661, 0.571 and 0.656 respectively, while a weak negative correlation coefficient of 0.106 was obtained for NO<sub>2</sub>. CH<sub>4</sub> had a strong significant positive correlation with relative humidity with a correlation coefficient of 0.859, while moderate correlation coefficients of -0.516 and 0.646 were obtained for NO<sub>2</sub> and CO<sub>2</sub> respectively, and a weak correlation coefficient of 0.345 was obtained for O<sub>3</sub>. CO<sub>2</sub> and CH<sub>4</sub> had a strong significant correlation with wind speed with correlation coefficients of 0.951 and -0.906 respectively, while a moderate negative correlation coefficient of 0.518 was obtained for O<sub>3</sub>, and a weak negative correlation coefficient of 0.317 was obtained for NO<sub>2</sub>. The predicted values of the meteorological parameters showed a significant level of agreement with their measured values. Therefore, among the atmospheric pollutants postulated as influencing meteorological parameters, CO<sub>2</sub> appears to be the most strongly significant in explaining temperature variations in this region of Niger Delta, with correlation coefficient of 96.2% and coefficient of determination (R<sup>2</sup>) of 0.926, implying that CO<sub>2</sub> influenced 92.6% variation in temperature in this part of Niger Delta within the period of investigation.
基金Council of Scientific and Industrial Research(CSIR)for providing the fellowship under CSIR-SRF scheme(P81101)。
文摘Vehicular emissions are considered one of the major anthropogenic sources of greenhouse gases and poor air quality in metropolitan cities.This study aims to see the correlation of CO_(2),CH_(4),and CO through monitoring over a period from December 2020 to October 2021 covering three seasons’winter,summer,and monsoon at two different traffic locations of Delhi having different traffic volumes,road patterns,and traffic management.The annual average morning concentration of CO_(2),CH_(4)and CO was found(533±105),(7.3±3.1),(10.7±3.0)ppm at Najafgarh and(480±70),(5.2±1.8),(7.8±2.8)ppm at Rajendra Place,respectively.A relationship between concentration of all three gases and meteorological parameters such as temperature,humidity,wind speed and wind direction has also been investigated using Pearson correlation coefficient and pollution rose diagram.A comparable pattern in concentration was observed for all three gases in spatial(location)and temporal(diurnal)distribution.The concentration trend of CO_(2)in different seasons is winter>summer>monsoon,while in the case of CH_(4)winter=summer>monsoon but not any seasonal trend was noted in CO case.It is observed that CO_(2)has a good relation with CO(a tracer for vehicular emission)in terms of diurnal variation,whereas,CH_(4)does not represent a relation with CO and CO_(2)diurnally,suggesting that vehicles are the source of CO_(2)but not much contributing to other greenhouse gases like CH_(4).
基金supported by the National Natural Science Foundation of China (No. 30670385)
文摘Dry deposition velocity of total suspended particles （TSP） is an effective parameter that describes the speed of atmospheric particulate matter deposit to the natural surface. It is also an important indicator to the capacity of atmosphere self-depuration. However, the spatial and temporal variations in dry deposition velocity of TSP at different urban landscapes and the relationship between dry deposition velocity and the meteorological parameters are subject to large uncertainties. We concurrently investigated this relationship at four different landscapes of Guangzhou, from October to December of 2009. The result of the average dry deposition velocity is （1.49 ± 0.77）, （1.44 ± 0.77）, （1.13 ±0.53） and （1.82± 0.82） cm/sec for urban commercial landscape, urban forest landscape, urban residential landscape and country landscape, respectively. This spatial variation can be explained by the difference of both particle size composition of TSP and meteorological parameters of sampling sites. Dry deposition velocity of TSP has a positive correlation with wind speed, and a negative correlation with temperature and relative humidity. Wind speed is the strongest factor that affects the magnitude of TSP dry deposition velocity, and the temperature is another considerable strong meteorological factor. We also find out that the relative humidity brings less impact, especially during the dry season. It is thus implied that the current global warming and urban heat island effect may lead to correlative changes in TSP dry deposition velocity, especially in the urban areas.
