Assessment of Transboundary PM2.5 from Biomass Burning in Northern Thailand Using the WRF-Chem Model.

Air pollution, particularly PM2.5, poses a significant environmental and public health concern, particularly in northern Thailand, where elevated PM2.5 levels are prevalent during the dry season (January-May).

Tracing vulnerable communities to ambient air pollution exposure: A geodemographic and remote sensing approach.

Most studies analyzing the effects of air pollution on disadvantaged populations use ground air quality measurements. However, ground stations are generally limited, with nearly 40% of countries having no official PM stations, not allowing air quality analysis for a significantly large share of the world's population. Furthermore, limited studies analyze community data from a geodemographic perspective, in other words, to delineate the sociodemographic profiles and geographically locate the socioeconomic groups more exposed to ambient air pollution.

Changing institutional landscape and transportation development in Dhaka, Bangladesh.

Cities in the global south, constrained by limited resources, face challenges in delivering efficient transportation infrastructure and services to support their rapidly growing urban populations. Dhaka, serves as an example, as it grapples with the increasing demand driven by population growth, exacerbated by factors like land and resource scarcity, as well as intricate geopolitical dynamics. Despite the construction of a metro rail and other similar mass transit options, Dhaka continues to face difficulties in meeting the increasing transportation demand, posing a persistent challenge.

Methane release from enteric fermentation and manure management of domestic water buffalo in Nepal.

Methane (CH) emission in livestock arises from enteric fermentation (EnF) and manure management (MM). This study develops the country-specific CH emission factors (EFs) in both EnF and MM for domestic water buffalo (Bubalus bubalis) and estimates total CH emission in Nepal using Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology. Seasonal field data were collected on morphological characteristics, feed characteristics, and manure management practices of the buffalo.

Environmental Factors Linked to Reporting of Active Malaria Foci in Thailand.

Thailand has made substantial progress towards malaria elimination, with 46 of the country's 77 provinces declared malaria-free as part of the subnational verification program. Nonetheless, these areas remain vulnerable to the reintroduction of malaria parasites and the reestablishment of indigenous transmission. As such, prevention of reestablishment (POR) planning is of increasing concern to ensure timely response to increasing cases.

Impact of climate change on agricultural production; Issues, challenges, and opportunities in Asia.

Agricultural production is under threat due to climate change in food insecure regions, especially in Asian countries. Various climate-driven extremes, i.e.

What is "hospital resilience"? A scoping review on conceptualization, operationalization, and evaluation.

Background: COVID-19 underscored the importance of building health systems and hospitals. Nevertheless, evidence on hospital resilience is limited without consensus on the concept, its application, or measurement, with practical guidance needed for action at the facility-level.

Aim: This study establishes a baseline for understanding hospital resilience, exploring its 1) conceptualization, 2) operationalization, and 3) evaluation in the empirical literature.

Evaluating the efficiency of coarser to finer resolution multispectral satellites in mapping paddy rice fields using GEE implementation.

Timely and accurate estimation of rice-growing areas and forecasting of production can provide crucial information for governments, planners, and decision-makers in formulating policies. While there exists studies focusing on paddy rice mapping, only few have compared multi-scale datasets performance in rice classification. Furthermore, rice mapping of large geographical areas with sufficient accuracy for planning purposes has been a challenge in Pakistan, but recent advancements in Google Earth Engine make it possible to analyze spatial and temporal variations within these areas.

Assessment of land use/land cover changes and its effect on land surface temperature using remote sensing techniques in Southern Punjab, Pakistan.

Land surface temperature (LST) is defined as a phenomenon which shows that microclimate of an urban system gets heated much faster than its surrounding rural climates. The expansion of buildings has a noteworthy influence on land use/land cover (LULC) due to conversion of vegetation land into commercial and residential areas and their associated infrastructure by which LST is accelerated. The objective of the research was to study the impact of changes in LULC on LST of Southern Punjab (Pakistan) through remote sensing (RS) data.

Growth and productivity assessments of peanut under different irrigation water management practices using CSM-CROPGRO-Peanut model in Eastern Mediterranean of Turkey.

Irrigation water scheduling is crucial to make the most efficient use of ever-decreasing water. As excessive irrigation decreases yield, while imprecise application also causes various environmental issues. Therefore, efficient management of irrigation frequency and irrigation level is necessary to sustain productivity under limited water conditions.

Using space-time scan statistic for studying the effects of COVID-19 in Punjab, Pakistan: a guideline for policy measures in regional agriculture.

Pakistan is included in top 50 countries which are estimated to face serious agriculture and food deficiency related challenges due to the worldwide pandemic coronavirus 2019 (COVID-19). The aim of this study was to evaluate the effects of COVID-19 on food supply chain and agriculture in Punjab, Pakistan, by using space-time scan statistic (STSS). A survey was conducted at 720 points in different districts of the province.

Understanding the nexus between public risk perception of COVID-19 and evacuation behavior during cyclone Amphan in Bangladesh.

In May 2020, when Bangladesh was struggling with community transmission of COVID-19, the country had to face the strongest tropical storm- Cyclone Amphan -which puts the evacuation process in jeopardy. Thus, it is crucial to measure the public risk perception about COVID-19 and its influence on the evacuation decision. This study explores the nexus between COVID-19 risk perception and coastal peoples' evacuation decisions during cyclone Amphan.

Effectiveness of containment strategies and local cognition to control vehicular traffic volume in Dhaka, Bangladesh during COVID-19 pandemic: Use of Google Map based real-time traffic data.

Background: To prevent the viral transmission from higher infected to lower infected area, controlling the vehicular traffic, consequently public movement on roads is crucial. Containment strategies and local cognition regarding pandemic might be helpful to control vehicular movement. This study aimed to ascertain the effectiveness of containment strategies and local cognition for controlling traffic volume during COVID-19 pandemic in Dhaka, Bangladesh.

Exploring potential of copper and silver nano particles to establish efficient callogenesis and regeneration system for wheat ( L.).

recalcitrance of wheat to regeneration is the major bottleneck for its improvement through callus-based genetic transformation. Nanotechnology is one of the most dynamic areas of research, which can transform agriculture and biotechnology to ensure food security on sustainable basis. Present study was designed to investigate effects of CuSO, AgNO and their nanoparticles on tissue culture responses of mature embryo culture of wheat genotypes (AS-2002 and Wafaq-2001).

Identification of risk factors contributing to COVID-19 incidence rates in Bangladesh: A GIS-based spatial modeling approach.

Background: COVID-19 pandemic outbreak is an unprecedented shock throughout the world, which has generated a massive social, human, and economic crisis. Identification of risk factors is crucial to prevent the COVID-19 spread by taking appropriate countermeasures effectively. Therefore, this study aimed to identify the potential risk factors contributing to the COVID-19 incidence rates at the district-level in Bangladesh.

Identification of factors influencing severity of motorcycle crashes in Dhaka, Bangladesh using binary logistic regression model.

Dhaka, the capital and megacity of the developing country Bangladesh, has experienced a sharp rise in motorcycle users in the last decade, especially after the introduction of ridesharing services. Therefore, the morbidity and mortality rates of motorcycle crash injuries have also increased and become one of the major safety concerns. However, there is scant empirical evidence on motorcycle crash severity in the context of developing countries.

Applications of GIS and geospatial analyses in COVID-19 research: A systematic review.

Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic.

An Open Label Pilot Study of a Brief Psychosocial Intervention for Disaster and Trauma Survivors.

Background: In the aftermath of disaster, a large proportion of people will develop psychosocial difficulties that impair recovery, but for which presentations do not meet threshold criteria for disorder. Although these adjustment problems can cause high distress and impairment, and often have a trajectory towards mental health disorder, few evidence-based interventions are available to facilitate recovery.

Objective: This paper describes the development and pilot testing of an internationally developed, brief, and scalable psychosocial intervention that targets distress and poor adjustment following disaster and trauma.

Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess).

The current influx of climate related information required scientists to communicate their findings to decision makers in governments, disaster preparedness organizations, and the general public. The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate many of the physical processes involved in the water cycle. This article presents the design, methods and development efforts to overcome some of the limitations of the previously developed SWAT visualization software programs by creating a set of modular web applications that can be duplicated, customized, and run.

Ground and satellite based observation datasets for the Lower Mekong River Basin.

In 'Satellite observations and modeling to understand the Lower Mekong River Basin streamflow variability' [1] hydrological fluxes, meteorological variables, land cover land use maps, and soil characteristics and parameters data were compiled and processed for the Lower Mekong River Basin. In this work, daily streamflow time series data at nine gauges located at five different countries in the Mekong region (Thailand, Laos People׳s Democratic Republic (PDR), Myanmar, Cambodia, and Viet Nam) is presented. Satellite-based daily precipitation and air temperature (minimum & maximum) data is processed and provided over the entire basin as part of the dataset provided in this work.

Monitoring green leaf tea quality parameters of different TV clones grown in northeast India using satellite data.

This study tries to quantify the effects of green leaf tea parameters that influence tea quality in Northeast India. The study is to identify the different parameters that have a significant influence on tea quality through the use of remote sensing. It investigates the methods for estimating tea quality based on remotely sensed Normalized Difference Vegetation Index (NDVI) data.