Subtropical Climate Region Research Articles

Tropical and temperate wastewater treatment plants assemble different and diverse microbiomes.

The diversity and assembly of activated sludge microbiomes play a key role in the performances of municipal wastewater treatment plants (WWTPs), which are the most widely applied biotechnological process systems. In this study, we investigated the microbiomes of municipal WWTPs in Bangkok, Wuhan, and Beijing that respectively represent tropical, subtropical, and temperate climate regions, and also explored how microbiomes assembled in these municipal WWTPs. Our results showed that the microbiomes from these municipal WWTPs were significantly different. The assembly of microbiomes in municipal WWTPs followed deterministic and stochastic processes governed by geographical location, temperature, and nutrients. We found that both taxonomic and phylogenetic α-diversities of tropical Bangkok municipal WWTPs were the highest and were rich in yet-to-be-identified microbial taxa. Nitrospirae and β-Proteobacteria were more abundant in tropical municipal WWTPs, but did not result in better removal efficiencies of ammonium and total nitrogen. Overall, these results suggest that tropical and temperate municipal WWTPs harbored diverse and unique microbial resources, and the municipal WWTP microbiomes were assembled with different processes. Implications of these findings for designing and running tropical municipal WWTPs were discussed. KEY POINTS: • Six WWTPs of tropical Thailand and subtropical and temperate China were investigated. • Tropical Bangkok WWTPs had more diverse and yet-to-be-identified microbial taxa. • Microbiome assembly processes were associated with geographical location.

Statistical Variability of Severe Rainfall Events in Southeastern Brazil

Extreme rainfall events are one of the natural phenomena that cause more damages. These events are known to be well localized, especially in tropical and subtropical climate regions such as southeastern Brazil. These events have high heterogeneity and the evolution of rain cells changes is quick, the forecast and knowledge of these extreme rainfall events still represent a challenge for the scientific community, such as the spatial variability of rainfall. For this, data from the weather radar installed in Campinas city were used, which generates new radar images every 10 minutes, and data from twenty-nine rain gauges located in the region. For this, 16 rainfall events were selected, located in the region of Campinas/SP, southeast of Brazil, a region that has already recorded many events. For this study, rain and intermittent zones were analyzed separately. This study helps to understand the main statistical characteristics of severe events, mainly located in the region of Campinas. In addition, the information extracted and the analyzes carried out in this study can be used as input data for models that generate possible rainfall scenarios, ensembles, such as, methods based on geostatistics or machine learning.

Investigation on the Thermal Condition of a Traditional Cold-Lane in Summer in Subtropical Humid Climate Region of China

A Chinese traditional narrow street, named Cold-Lane, can create a microclimatic zone that provides pedestrian thermal comfort under hot and humid climate conditions. This phenomenon was observed through experimental measurement during the summer of 2016. The heat transfer rate over the pedestrian body surface was calculated to reveal why pedestrians experience a cool sensation, and computational flow dynamics (CFD) simulation was carried out to study the influence of the street aspect ratio on the shading effect. It was found that the perception of thermal comfort can be attributed mainly to the radiation between the relatively cool surrounding walls and the human body, and the wind velocity has little effect on sensible heat dissipation. The cool horizontal and vertical surfaces in the street canyon are mainly due to the shading effect as a result of the small aspect ratio, which is a typical characteristic of the traditional Chinese street. The shading effect of the high walls on both sides creates the cooling effect of this narrow street.

Thermo-Environmental Assessment of a Heated Venlo-Type Greenhouse in the Yangtze River Delta Region

Accurate evaluation of microclimate conditions in a greenhouse can assist producers to manage crop production and designers to optimize climate control systems. An assessment of the variable thermo-environmental behavior of a heated Venlo-type greenhouse under the influence of naturally changing climate conditions in the Yangtze River Delta region was undertaken. A three-dimensional transient computational fluid dynamics (CFD) model was developed to analyze the airflow pattern and dynamic distribution of temperature and humidity inside the greenhouse. Validation of the numerical model showed a satisfactory agreement between measured and simulated values of air velocity, temperature, and absolute humidity, with mean hourly air temperature mean absolute error (MAE) and root mean square error (RMSE) values of 7.7% and 7.9%, respectively, and mean hourly air humidity MAE and RMSE values of 16.18% and 16.42%, respectively. Simulation results demonstrated that the airflow pattern shaped the distribution of temperature and absolute humidity, and homogeneity of both variables was prevalent inside the greenhouse. These results could be adopted by growers and designers in the Yangtze River Delta region and other sub-tropical climatic regions to improve crop production and optimize climate control systems.

Seroprevalence and risk factor analysis of human leptospirosis in distinct climatic regions of Pakistan

Background: Leptospirosis is a worldwide emerging infectious disease of zoonotic importance and large epidemics and epizootics have been reported all over the globe. Methods and materials: A cross survey study was conducted to estimate seroprevalence of human leptospirosis in climatically distinct regions of Pakistan and to identify the risk factors associated with the disease. Blood samples from 360 humans were collected through convenient sampling, 120 from each of three study areas. Serological testing was performed using ELISA kit as per manufacturer's recommendations. Results: The results showed an overall prevalence of 40.83% (95% CI; 35.71–46.11). Statistical analysis showed significant (p < .05) differences in leptospiral seroprevalence in three different geographic locations, with highest in humid sub-tropical climatic region (50.83%; 95% CI; 41.55–60.07), followed by semi-arid region (44.16%; 95% CI; 35.11–53.52) and lowest in hot and dry region (27.50%; 95% CI; 19.75–36.40). After multivariate analysis age, gender, exposure to flooding water, source of water usage, disinfection schedule of surroundings and history of cut and wound were found significantly associated with the seropositivity of Leptospira. Conclusion: The present study, first to uncover seroprevalence of human Leptospira in different climatic regions of Pakistan, alarms about effect of climate on prevalence of Leptospira in the region.

White Leaf Spot Caused by Neopseudocercosporella capsellae: A Re-emerging Disease of Brassicaceae.

White leaf spot can cause significant damage to many economically important Brassicaceae crops, including oilseed rape, vegetable, condiment, and fodder Brassica species, and recently has been identified as a re-emerging disease. The causal agent, Neopseudocercosporella capsellae, produces foliar, stem, and pod lesions under favorable weather conditions. N. capsellae secretes cercosporin, a non-host specific, photo-activated toxin, into the host tissue during the early infection process. The pathogen has an active parasitic stage on the living host and a sexual or asexual saprobic stage on the dead host. Where the sexual stage exists, ascospores initiate the new disease cycle, while in the absence of the sexual stage, conidia produced by the asexual stage initiate new disease cycles. Distribution of the pathogen is worldwide; however, epidemiology and disease severity differ between countries or continents, with it being more destructive in Subtropical, Mediterranean, or Temperate climate regions with cool and wet climates. The pathogen has a wide host range within Brassicaceae. Brassica germplasm show varied responses from highly susceptible to completely resistant to pathogen invasion and significant susceptibility differences are observed among major crop species. Cultural practices only provide effective disease control when the climate is not conducive. An increase in the susceptible host population and favorable weather conditions have together favored the recent rise in white leaf spot disease occurrence and spread. The lack of understanding of variation in pathogen virulence and associated resistant gene sources within brassicas critically limits the potential to develop efficient control measures.

Diversity of banana diploid hybrids: An assessment based on a hydroponic system

AbstractBananas are typical to tropical and subtropical climate regions, where they have better conditions due to high air humidity and soil water availability. The production of drought‐tolerant varieties is an alternative to expand the cultivation sites to drier areas. In this work, we present a hydroponic system for the genotype selection of Musa sp. (AA) subjected to water stress. A total of 14 banana genotypes were tested; 12 diploids and two commercial varieties with a known response to drought tolerance. The results show that the improved diploids have different responses with respect to water deficit, with the PMGB043 and PMGB044 genotypes considered more susceptible and the PMGB075 and PMGB099 genotypes more tolerant. Under water deficit conditions, most banana diploids maintain a high relative water content, but there is a reduction in aerial part growth and an increase in root dry mass. The accumulation of alcohol dehydrogenase, especially in control treatment plants, indicate that the glycolytic pathway was used to supply energy demand, showing potential flood‐tolerant genotypes. The results are essential for the preimprovement of banana cultivars.

Investigation on Wintry Thermal Comfort in Traditional Houses of Nepalese Three Climatic Regions

The traditional houses are well adapted to the climate and socio-culture using local building materials and techniques. However, traditional practices are being replaced by the artificial materials, modern design and new technology. It requires strong policies to sustain the traditional architecture. The objectives of this study are to evaluate the thermal condition of traditional houses and to estimate the comfort temperature of residents. The thermal comfort survey was conducted during winter in the traditional houses. The thermal sensation votes were collected from 275 people in cold, temperate and sub-tropical climatic regions. This study was revealed that the mean indoor air temperature in cold climatic region is 12.3°C, which was 9.5K and 4.4K lower than sub-tropical and temperate climates. The comfort temperature of the residents in the cold climate was 13.9°C, which was 8.8K and 3.8K lower than sub-tropical and temperate climates. The mean clothing insulation in cold climate was 1.63 clo which was 0.48 clo and 0.31 clo higher than sub-tropical and temperate climates. It concludes that the people were well adapted to each climate with clothing adjustments and made themselves satisfied with the thermal condition of their houses.

Energy Conservation and Consumption Reduction in Residential Quarters: Taking Cuihu Garden Residential District in Pingxiang City as an Example

This paper uses Auto-Revit for an energy assessment of Cuihu Garden Residential District located in Anyuan District, Pingxiang City, Jiangxi Province. Comparative analysis of building energy consumption before and after energy-saving renovation. Through simulation analysis, it can be concluded that replacing LED light sources, enhancing natural ventilation efficiency, and increasing green roof construction can effectively reduce building energy consumption. This article draws the following conclusions: Firstly, by replacing the LED light source, the energy of the residents in the community can be reduced by 65.2%; secondly, the combination of mechanical ventilation and natural shaft ventilation can reduce 73kWh of electricity in ten hours; finally, the green roof energy effectively alleviate temperature changes on the surface of the building, and indirectly reduce the power consumption of heating and air conditioning in the building. The research results can serve as a reference for the improvement of building energy efficiency in cities with subtropical monsoon climate regions represented by Pingxiang City. The direction of energy-saving improvement can be extended to inland small cities in the country and the world.

Spatial Variation of Land Use/Cover Composition and Impact on Surface Urban Heat Island in a Tropical Sub-Saharan City of Accra, Ghana

Rapid urbanization is one of the most crucial issues in the world of the 21st century. Notably, the urban heat island phenomenon is becoming more prominent in megacities and their hinterlands in temperate and subtropical climatic regions. In the daytime in summer, there exists a high possibility of accelerating the land surface temperature (LST) in desert cities, due to the alterations made by human beings in the natural environment. In this study, we investigate the spatial formation of LST in a tropical sub-Saharan city of Accra, a gateway to West Africa, using Landsat data in 2003 and 2017. Machine learning techniques and the different spatial and statistical methods such as tasseled cap transformation (TCT), urban-rural gradient, and multiresolution grid-based and landscape metrics were employed to examine procured land use/cover (LUC) and LST maps. LUC was classified into five categories: Built up, Green 1, Green 2, Bare land, and Water. The results of the analysis indicate that Built up, Green 2, and Bare land had caused the highest heating effect while Green 1 and Water had caused the considerable cooling effect during the daytime in Accra. The urban-rural difference in LST recorded 1.4 °C in 2003 and 0.28 °C in 2017. The mean size, mean shape, largest patch, and aggregation of Built up, Green 1, and Green 2 had a strong relationship with the mean LST. It is essential for urban planners to carefully examine the formation and effect of the urban heat island (UHI) for sustainable urban development and landscape policy toward mitigation and adaptation planning in Accra.

Physico-chemical characterization of wines produced by different rootstock and Vitis vinifera cv. Tannat clones in vineyards of subtropical climate region

Tannat wine trees are well characterized in Uruguay and the French region of Madiran for their high colour and phenolic concentrations. In addition to the cultivar, the rootstock, clone and region of production can influence the phenolic concentrations of wines. In this context, this study evaluated the rootstocks 'SO4' (Vitis berlandieri x Vitis riparia), 'Gravesac' ('161-49C' x '3309C') and '3309C' (Vitis riparia x Vitis rupestris) grafted with Tannat cultivar clones ('Californian', '944', '717', '398' and '794') to assess the physicochemical, phenolic and sensorial composition of the wine produced in the Campanha Gaúcha (RS) region, Southern Brazil, in a subtropical climate region. A vineyard planted in 2007 was used in this study (for 3 years during 2015, 2016 and 2017). The wine composition and the sensorial profile were evaluated as dependent variables. This study showed that the rootstocks and the Tannat clones did not influence the dependent variables evaluated and that the genetic materials and their combinations presented high oenological potential, providing wines with high alcohol content, colour and phenolic compound concentrations. This study suggests the diversification of rootstocks and clones as a way of increasing genetic variability, avoiding the cultivation of a single rootstock and clone.

Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones

Accurate prediction of reference evapotranspiration (ET0) is essential for efficient planning and management of limited water resources through proper irrigation scheduling. The FAO-56 Penman-Monteith approach to ET0 estimation was adopted to compute ET0 from data obtained in a subtropical climatic region in Bangladesh. Quantified ET0 values along with the meteorological variables for two other Stations located in south Florida, USA, were directly obtained from the USGS website. A commonly used machine learning algorithm, Adaptive Neuro Fuzzy Inference System (ANFIS), was employed to predict daily ET0 using regional meteorological data (e.g., daily maximum and minimum air temperatures, wind speed, relative humidity, sensible heat flux, latent heat and sunshine duration). Four optimization algorithms were employed to tune ANFIS, resulting in hybrid models: Biogeography-based Optimization (BBO-ANFIS), Firefly Algorithm (FA-ANFIS), Particle Swarm Optimization (PSO-ANFIS), and Teaching-Learning-based Optimization (TLBO-ANFIS). These models’ performances were compared with the standard ANFIS model with parameters tuned using an Integrated Least Squares and Backpropagation Gradient Descent (LSGD) algorithm. Decision theories were applied to assess the accuracy of the predictions as well as to rank prediction models based on eight statistical indices. Results indicated that FA-ANFIS resulted in the most accurate ET0 predictions. In the next stage, ensembles of these prediction models were compared to determine whether the ensemble models resulted in more reliable predictions than the standalone models. To develop each ensemble, three decision theories were applied: Shannon’s Entropy, Coefficient of Variation, and Grey Relational Analysis. All three ensemble approaches provided similar results, showing ensemble prediction methods to perform better than most individual models.

Compositional Nutrient Diagnosis (CND) Applied to Grapevines Grown in Subtropical Climate Region

Soil analysis is used to estimate nutrient availability, but nutrient concentrations are not always related to yield in most fruit plants, including grapevines. Thus, additional multivariate mathematical models, such as the compositional nutrient diagnosis (CND), which takes into account leaves nutrient concentration, and yield, can contribute to estimating critical levels or sufficiency bands of elements, as well as to detect deficiency and/or excess of nutrients. The aim of the present study was to establish CND standards, and the critical level and sufficiency band of nutrients, in the grapevine Vitis vinifera L., grown in a subtropical climate region. Leaves were collected in 81 vineyards in the Campanha Gaúcha do Rio Grande do Sul region, Southern Brazil, and analyzed for macro- and micro-nutrient concentration. The yield of each vineyard was assessed. Grapevine nutritional status was calculated through the CND method. CND-r2 indices were effective in establishing the nutritional status of grapevines for macro- and micro-nutrients as sub-optimal, excessive, or balanced. The CND methodology established the critical level and sufficiency bands of nutrients more accurately than the current recommendations for grapevines. Multi-nutrient associations were more effective than the single nutrient determination in defining the threshold of a given nutrient that can reduce grapevine yield.

Evaluation of Different Roof Materials for the Mitigation of Urban Warming in a Subtropical Monsoon Climate

AbstractDifferent roof materials are deployed for mitigating the urban heat, which significantly affects our life. However, the answer to the question of which roof material has the best cooling performance in urban areas remains uncertain. We need to compare different roof materials together under a certain climate condition to find geographically appropriate mitigation strategies. This study performs field experiments using four different roof materials (gray, white, and grass surfaces, and rooftop solar panel) to evaluate their effectiveness on temperature reductions in a subtropical monsoon climate region from December 2017 to July 2018. The results show that the white surface reduced the average daily surface temperature by 3.37 °C. This cooling effect increased with the increase in surface albedo and incoming solar radiation. On the other hand, the average cooling effect of the grass surface was much lower (0.43 °C). This is attributable to the low soil moisture, which was influenced by the monsoon, thereby indicating that the adoption of grass roofs requires consideration of the availability of water resources even in humid regions. The solar panel reduced the daily surface temperature by 0.59 °C but exerted strong warming effect (7.36 °C) during midday and cooling effect (4.03 °C) during midnight because of its low albedo, low emissivity, and low heat capacity. Our results suggest that the grass roof with a native plant species is still not comparable with the white roof for mitigating urban heat in a subtropical monsoon climate under the present climatic conditions and especially for drier climates predicted for the future, and rooftop solar panels may heat the urban atmosphere by their warm surface during daytime.

The effect of trees on human energy fluxes in a humid subtropical climate region.

Trees are considered to be an effective tool for improving human thermal comfort in hot climates and have been widely used in landscape architecture. However, it is not always clear how trees affect human-environment energy fluxes. In this study, an in-depth analysis of four common tree species was undertaken based on comprehensive field measurements, in terms of how each tree and its characteristics affected the energy fluxes of a person in a humid subtropical climate region. Results showed that the largest effect of trees was on radiation fluxes, with a much smaller effect on the convective and evaporative fluxes. For a person standing in shade, a tree can reduce approximately 25% of the absorbed radiation compared with an open reference point. Moreover, the cooling effect on radiation components was found to be greater in the solar radiation domain than in the terrestrial radiation domain. Solar radiation and ground surface temperature had the largest effect on a human energy budget, which was affected by characteristics of the trees and the thermophysical properties of ground surfaces. The effect from relative humidity and wind speed was quite minimal. For the four common tree species in this study, Ficus microcarpa had the best thermal performance by reducing the most absorbed solar radiation flux. This study shows a detailed empirical research about the thermal effects of trees on a person, providing recommendations for tree species selection in urban design.

Potential of RT, bagging and RS ensemble learning algorithms for reference evapotranspiration prediction using climatic data-limited humid region in Bangladesh

Ensemble learning (EL), an alternative approach in the machine-learning field, offers an accurate reference evapotranspiration (ETo) prediction, which is of paramount significance for the hydrological studies and agricultural water practices. Although the FAO-56 Penman-Monteith (PM) equation is regarded as an ideal model for estimating ETo, its applicability is limited due to the absence of required climatic datasets in many regions of the world. Despite its significance, only a few studies use the EL algorithms for the ETo prediction perspective. In this study, we contribute to fill this gap from a two-fold way. First, we present the potential of new EL Random Tree (RT), Bagging and Random Subspace (RS) algorithms which were compared with two commonly used Random Forest (RF), and Support Vector Machine (SVM) algorithms for predicting daily ETo with the climatic data-limited humid region in Bangladesh during 1983–2017 using a five-fold cross-validation scheme. Second, we explore the role of contributing variables influencing ETo change at the regional scale. When a lack of climatic datasets, Tmax (maximum temperature), Tmin (minimum temperature) and Rs (solar radiation) as 3 input combinations obtained the reasonable precision for estimating ETo in all climatic regions except for south-central and south-western regions. Compared to other state-of-arts models, the RT model performed superior to predict ETo in all input combinations followed by the RF, Bagging, RS, and SVM. Considering less difficulty level, high prediction accuracy, more dependability and fewer computation costs of studied models, RT and RF models have been suggested as the promising potentials for daily ETo estimate in subtropical climate regions of Bangladesh and also may be applicable worldwide in the similar climates. The importance analysis from the RF model depicted that the wind speed (U2) and solar radiation (Rs) are the largest influential variables affecting the observed and predicted daily ETo changes in Bangladesh.

Applications of remote sensing and GIS for watershed characterization and soil loss assessment of tons watershed in Dehradun, Garhwal Himalaya

Watershed characterization is the most important part of watershed management which includes soil loss, soil loss assessment indicates the amount of soil loss or erosion in ton/hectare/ year through applying to Geospatial techniques as Remote sensing and GIS. The agricultural land is being lost by manmade as well natural whereas manmade or anthropogenic factor accelerates erosion of soil. It is a worldwide phenomenon leading to loss of decrease of water table availability for plants, increases runoff from the more impermeable subsoil, and loss of nutrients from the soil. Watershed management and assessment of soil loss are most helpful for planning and batter management in a watershed and planning units. Remote sensing and GIS along with the satellite image-based model approach provides a scientific, quantitative, and applied result. It can compute a consistent outcome of soil erosion and sediment yield for a wide range of areas under all climatic circumstances. Revised Universal Soil Loss Equation (RUSLE) apply to soil loss, which is integrated with Remote Sensing and GIS in Tons watershed lies between 77°56’05” E to 78°01’01” East longitude and 30° 21’05” N to 30°26’51” North latitude, having 97.02 km2 area (9,702 hectares) under the sub-tropical climatic region of Uttarakhand. The present case study based on computational with software and geospatial technologies results come i.e. A = is the computed soil loss per unit area, R = is the rainfall erosivity, K = is the soil erodibility factor, L = is the slope-length factor, C = is the cover and management factor, P = is the support practice factor. The rainfall erosivity (R=87.5 + 0.375 × R), C P is under range 0.006-0.8, Soil Erosion Risk range is slight to High 51.40% and 0.85% total area of the study region. Average annual soil loss ton/ha/year indicated in different land-use classification as lowest soil loss found in River bed (0.17 ton/ha/year) and highest shown in the open forest (56.58 ton/ha/year) in 2016. The study area comes under a low probability zone and partially comes under a moderate and moderate-high zone. The case study can be highly recommended and will help to implementation of management of soil loss and soil conservation practice in the Tons watershed as well as Himalayan regions. Keywords: RUSLE, Tons Watershed, Soil Loss, Remote Sensing &amp; GIS, Garhwal Himalaya.

Five years’ exposure of elevated atmospheric CO2 and temperature enriched recalcitrant carbon in soil of subtropical humid climate

Atmospheric CO2 and temperature levels are predicted to increase to 550 μmol mol−1 and by 2.0–4.5 °C higher than the present, respectively, by the middle of the 21st century. Our experiment was focused to study the impact of elevated atmospheric carbon dioxide (CO2) (500 ± 20 ppm) and temperature (> 2 °C than ambient) and their association on soil respiration and total organic carbon (TOC) along with its different pools such as: active pool (AP), passive pool (PP), particulate organic carbon (POC) and mineral-associated organic carbon (MOC) in 0−30 cm soil depth under field based open-top chambers for 5years (2011–2016). Elevated CO2 (eCO2), elevated temperature (eTemp) and their association (eCO2+eTemp) resulted in significant 3.09, 11.1 and 2.76 % reduction in TOC, respectively, in 0−30 cm soil depth over ambient condition. In all predicted climatic conditions, depletion of AP and POC were observed. Conversely, carbon enriched in PP and MOC. The outcome of the soil respiration study revealed that even though cumulative carbon mineralization values were lower in soil exposed to eCO2 and eTemp, under carbon depleted condition, the carbon mineralization efficiencies were higher. So, it can be concluded that in future climate scenario soil will act as a net source to atmospheric CO2 in subtropical humid climatic regions.

Analysis of the Effect of Phase Change Material on Indoor Temperature in Subtropical Climate Region

Analysis of the Effect of Phase Change Material on Indoor Temperature in Subtropical Climate Region

INTER-COMPARISON BETWEEN MODIS SATELLITE-BASED AND AERONET GROUND-BASED AEROSOL OPTICAL DEPTH PRODUCTS IN VIETNAM

Although a number of studies have extensively inter-compared the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-based aerosol optical depth (AOD) with the Aerosol Robotic Network (AERONET) ground-based AOD on both global and regional scales, almost no similar studies have been conducted for Vietnam - a humid subtropical climate region. For the first time, inter-comparison between the MODIS Terra and Aqua Collection 6.1 (C6.1) Dark Target (DT) 10 km, Deep Blue (DB) 10 km, and merged DT-DB 10 km with the AERONET AODs has been performed in different areas with different surface types and different climatic characteristics in Vietnam. Three investigated AERONET stations are Nghia Do (urban), Son La (mountainous rural), and Bac Lieu (coastal urban) with the studying periods of 2010 - 2016, 2012 - 2017, and 2010 - 2017, respectively. Our findings showed the better performances of DB algorithm than those of DT and DT-DB products in the urban area. Additionally, all MODIS AOD algorithm performed worse over the coastal area compared to those in the non-coastal areas. Generally, the ability of all the MODIS AODs to catch up the monthly-mean AERONET AODs has been expressed in this study.