Vegetation response to extreme climate events on the Mongolian Plateau from 2000 to 2010

Climate change has led to more frequent extreme winters (aka, dzud) and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–dzud and 2010 dzud were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between �1.5 and �0.5 and were statistically different (P \u3c 0:001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (p \u3c 0:001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI \u3c �1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (R2 D 65 and 60, p \u3c 0:05) than for the IM grassland biome (R2 D 53, p \u3c 0:05). Our results showed significant differences in the responses to extreme climatic events (summer drought and dzud) between the desert and grassland biomes on the Plateau

Estimating stand volume and above-ground biomass of urban forests using LiDAR

Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR). In this study we assessed forest stand volume and above-ground biomass (AGB) in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA) and mean stand height (H) from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first) (proxy of BA) and the 95th percentile of the distribution of all first returns (proxy of H). The R2 were 0.81 (p < 0.01) for the stand volume model and 0.77 (p < 0.01) for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3%) and 19.59 Mg·ha−1 (23.9%), respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H), which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods

Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model

We developed a water-centric monthly scale simulation model (WaSSI-C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI-C model was evaluated with basin-scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE) estimates by multiple independent methods across 2103 eight-digit Hydrologic Unit Code watersheds in the conterminous United States from 2001 to 2006. Our results indicate that WaSSI-C captured the spatial and temporal variability and the effects of large droughts on key ecosystem fluxes. Our modeled mean (±standard deviation in space) ET (556 ± 228 mm yr−1) compared well to Moderate Resolution Imaging Spectroradiometer (MODIS) based (527 ± 251 mm yr−1) and watershed water balance based ET (571 ± 242 mm yr−1). Our mean annual GEP estimates (1362 ± 688 g C m−2 yr−1) compared well (R2 = 0.83) to estimates (1194 ± 649 g C m−2 yr−1) by eddy flux-based EC-MOD model, but both methods led significantly higher (25–30%) values than the standard MODIS product (904 ± 467 g C m−2 yr−1). Among the 18 water resource regions, the southeast ranked the highest in terms of its water yield and carbon sequestration capacity. When all ecosystems were considered, the mean NEE (−353 ± 298 g C m−2 yr−1) predicted by this study was 60% higher than EC-MOD\u27s estimate (−220 ± 225 g C m−2 yr−1) in absolute magnitude, suggesting overall high uncertainty in quantifying NEE at a large scale. Our water-centric model offers a new tool for examining the trade-offs between regional water and carbon resources under a changing environment

Advances in air quality research – current and emerging challenges

This review provides a community's perspective on air quality research focusing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizing sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions, and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground-based and remote sensing instruments, including in particular those on satellites. The research should also capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposure to air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high-resolution distributions of these metrics over cities. The review also examines how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy

Albedo changes caused by future urbanization contribute to global warming

The replacement of natural lands with urban structures has multiple environmental consequences, yet little is known about the magnitude and extent of albedo-induced warming contributions from urbanization at the global scale in the past and future. Here, we apply an empirical approach to quantify the climate effects of past urbanization and future urbanization projected under different shared socioeconomic pathways (SSPs). We find an albedo-induced warming effect of urbanization for both the past and the projected futures under three illustrative scenarios. The albedo decease from urbanization in 2018 relative to 2001 has yielded a 100-year average annual global warming of 0.00014 [0.00008, 0.00021] °C. Without proper mitigation, future urbanization in 2050 relative to 2018 and that in 2100 relative to 2018 under the intermediate emission scenario (SSP2-4.5) would yield a 100-year average warming effect of 0.00107 [0.00057,0.00179] °C and 0.00152 [0.00078,0.00259] °C, respectively, through altering the Earth’s albedo

Measuring the patient perspective on latissimus dorsi donor site outcomes following breast reconstruction.

BACKGROUND: There is little evidence about the long-term donor site outcome of latissimus dorsi breast reconstruction and no patient-reported outcome measures designed specifically for the procedure. METHODS: A prospective cohort of breast cancer patients having latissimus dorsi reconstruction after a mastectomy was recruited from 270 hospitals in the United Kingdom. An 18-month follow up questionnaire containing two novel scales was sent to consenting patients. The prevalence of aesthetic and functional morbidity at the donor site was described. The two new scales were refined using the Rasch measurement model and subsequently validated. RESULTS: 1,096 women completed the new scales. 78% of patients reported that no back appearance issues had bothered them "most of the time" or "all of the time" in the past two weeks. The equivalent figure for functional morbidity was 60%. Four items were eliminated following initial psychometric testing. This produced an 8-item Back Appearance scale and an 11-item Back and Shoulder Function scale. Both scales showed adequate fit to the Rasch measurement model. Higher levels of aesthetic and functional bother were observed for completely autologous procedures versus those where latissimus dorsi reconstruction was used to cover an implant (p <0.05). Higher levels of aesthetic bother were observed in women who had suffered a perioperative complication at the donor site (p = 0.003). CONCLUSION: These results can inform patients of the morbidity associated with latissimus dorsi reconstruction. The new scales can be used to compare groups undergoing different variations of the procedure and to monitor individual patients

Policy shifts influence the functional changes of the CNH systems on the Mongolian plateau

By applying the concept of the coupled natural and human system (CNH), we compared spatiotemporal changes in livestock (LSK), land cover, and ecosystem production to understand the relative roles that natural and social driving forces have on CNH dynamics on the Mongolia plateau. We used socioeconomic and physical data at prefecture level for Inner Mongolia and Mongolia from 1981 through 2010 to represent changes in net primary productivity (NPP), enhanced vegetation index (EVI), precipitation, annual average temperature, LSK, livestock density (LSKD), land cover change (LCC), gross domestic production (GDP), and population (POP). The ratios such as LSK:NPP, LSKD: EVI, LSKD:albedo, LSK:POP, and LSK:GDP were examined and compared between Inner Mongolia and Mongolia, and structural equation modeling (SEM) was applied to quantify the complex interactions. Substantial differences in LSK, POP, and economic development were found among the biomes and between Inner Mongolia and Mongolia. When various indicators for policy shifts—such as the World Trade Organization (WTO) for China, the Third Campaign to Reclaim Abandoned Agriculture Lands (ATAR-3), and the Grain for Green Program for China (GFG)—were added into our SEM, the results showed significant change in the strength of the above relationships. After China joined the WTO, the relationships in Inner Mongolia between LSKD:LCC and LSKD:NPP were immensely strengthened, whereas relationships in NPP:LCC were weakened. In Mongolia, the ATAR-3 program first appeared to be an insignificant policy, but the Collapse of the Soviet Union enhanced the correlation between LSKD:LCC, weakened the connection of LCC:NPP, and did not affect LSKD:NPP. We conclude that human influences on the Mongolian CNH system exceeded those of the biophysical changes, but that the significance varies in time and per biome, as well as between Inner Mongolia and Mongolia

Toward ‘Vaccine Internationalism’: The Need for an Equitable and Coordinated Global Vaccination Approach to Effectively Combat COVID-19

From Frontiers via Jisc Publications RouterHistory: collection 2021, received 2021-03-10, accepted 2021-03-15, epub 2021-04-14Publication status: Publishe

Advances in air quality research – current and emerging challenges

© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License. https://creativecommons.org/licenses/by/4.0/This review provides a community’s perspective on air quality research focusing mainly on developmentsover the past decade. The article provides perspectives on current and future challenges as well asresearch needs for selected key topics. While this paper is not an exhaustive review of all research areas in thefield of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizingsources and emissions of air pollution, new air quality observations and instrumentation, advances in air qualityprediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure andhealth assessment, and air quality management and policy. In conducting the review, specific objectives were(i) to address current developments that push the boundaries of air quality research forward, (ii) to highlightthe emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guidethe direction for future research within the wider community. This review also identifies areas of particular importancefor air quality policy. The original concept of this review was borne at the International Conferenceon Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the articleincorporates a wider landscape of research literature within the field of air quality science. On air pollutionemissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources,particulate matter chemical components, shipping emissions, and the importance of considering both indoor andoutdoor sources. There is a growing need to have integrated air pollution and related observations from bothground-based and remote sensing instruments, including in particular those on satellites. The research shouldalso capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which areregulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue,with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time,one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerablepotential by providing a consistent framework for treating scales and processes, especially where thereare significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposureto air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of moresophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments.With particulate matter being one of the most important pollutants for health, research is indicating the urgentneed to understand, in particular, the role of particle number and chemical components in terms of health impact,which in turn requires improved emission inventories and models for predicting high-resolution distributions ofthese metrics over cities. The review also examines how air pollution management needs to adapt to the abovementionednew challenges and briefly considers the implications from the COVID-19 pandemic for air quality.Finally, we provide recommendations for air quality research and support for policy.Peer reviewe