Environmental Research Letters最新文献

Addressing the mounting plastic waste problem requires system-level solutions, along with interventions that promote behavioral change. In low-resource countries, inadequate, if not absent, waste management systems lead to unsafe disposal practices, including open burning. While theory-informed approaches are essential for identifying enablers and barriers to target behavior change, their application is limited in these settings. Given the lack of a theory-driven synthesis of behavioral strategies to address plastic waste, this systematic review aimed to: (1) synthesize behavioral interventions related to plastic waste management in low-resource countries; (2) map these interventions to the behavior change wheel (BCW), using the capability-opportunity-motivation-behavior model, and the theoretical domains framework (TDF); and (3) classify implementation strategies to inform theory-driven intervention design. This review is the first to use the BCW to examine behavioral interventions related to plastic waste management in low-resource countries. Nine bibliographic databases: APA PsycInfo, CINAHL, Embase, Environment Complete, Global Health, GreenFile, Health Source: Nursing Academic, PubMed, and Web of Science Core Collection were searched. We included English-language human studies up to 9 April 2025, that evaluated interventions or policies targeting individual- or community-level behaviors related to plastic waste management in low-, lower-middle, or upper-middle income countries. We excluded studies from high-income countries, and those focused on environmental impacts, industrial or municipal waste streams, ecosystems or animals without human behavioral components, COVID-19-specific waste, or hypothetical modeling without real-life interventions. Forty-three studies met the inclusion criteria. Study quality was assessed using the mixed methods appraisal Tool. Interventions spanned 27 low-resource countries and targeted diverse populations, including schoolchildren, households, market vendors, and community organizations. Education was the most frequent BCW intervention function (76.7%), followed by environmental restructuring, incentivization, persuasion, and training. Mapping revealed that behavioral interventions relied most frequently on the TDF domains of environmental context, knowledge, skills, and social influences. Some domains, such as beliefs about capabilities, reinforcement, and identity, received moderate attention, while appealing to emotion or the use of behavioral regulation, were underutilized. Behavioral interventions for plastic waste management in low-resource countries have predominantly emphasized awareness-raising but insufficiently leveraged other BCW intervention functions and TDF domains. Integration of motivational, emotional, and identity-based strategies alongside structural support can enhance the sustainability of behavior change.

Multiple cropping increases land productivity by allowing multiple harvests per year, offering production gains without cropland expansion. Irrigation is especially critical in the seasonally dry tropics, enabling multiple cropping where otherwise only a single rainfed cycle would be feasible. Estimates of the current state of multiple cropping and the multiple cropping expansion potential without changes in irrigation patterns exist, but the multiple cropping expansion potential through irrigation expansion has not yet been assessed at the global scale. Here, we estimate multiple cropping expansion potentials on existing cropland considering the interaction with irrigation and local water availability constraints to determine how much cropland area can be managed in multiple cropping systems and the associated increases in annual yields and crop production. We find that, under current climatic conditions, there is considerable global biophysical potential to expand multiple cropping on existing cropland, particularly when also expanding irrigation. Total global crop production could increase by 28% (from 4 200 mio. t DM to 5 400 mio. t DM). This gain stems from nearly quadrupling the area under rainfed multiple cropping, more than doubling multiple cropping area within already irrigated lands, and expanding irrigation into areas where it facilitates another growing season. Our study reveals a considerable multiple cropping expansion potential on existing cropland that-when tapped-could contribute to averting further cropland expansion to meet future demand for agricultural outputs. Local irrigation water availability constrains the irrigation-enabled multiple cropping potential, implying that the interaction of multiple cropping and irrigation is crucial to consider in comprehensive land and water assessments that account for biophysical and socio-economic constraints, sustainability criteria, and land competition under future global change.

Livestock underpin livelihoods and food security in Africa, using marginal lands to produce high-quality protein for the household or as a source of income. For mixed farmers, livestock provide draught power, manure for fields, and buffer variations in crop productivity. Livestock also hold cultural significance. However, African livestock farmers are especially vulnerable to climate hazards, and attempt to reduce impacts in different ways, with varied outcomes. A synthesis of the state of knowledge of livestock farmers' responses to climate variability and change would assist policymakers and practitioners to make informed decisions, and guide researchers towards gaps that need to be filled. To that end, we systematically reviewed articles published between 2014 and 2022-the period between the end of the Intergovernmental Panel on Climate Change's Fifth Assessment and the end of the Sixth, recording study metadata, farmers' responses, and their drivers, outcomes, barriers and enablers. We included 186 articles from 32 countries (most frequently Kenya or Ethiopia), from which 1089 responses were coded for analysis. Responses by small-scale farmers of cattle, sheep and goats, typically as part of mixed crop-livestock systems, were most common (n = 816), with few documented responses of commercial farmers (121). Most responses pertained to changing herd management (437), followed by feed or pasture management (294). Drought was the most common climate driver of responses (567), while the most commonly mentioned barriers included financial constraints (116), a lack of knowledge or information (98), and government support (67). While there is a sizable body of literature on climate impacts and adaptation of livestock farmers, notable gaps included any work in Central and Northern Africa, and responses of commercial farming systems. In general, future research should focus on these gaps and on improving the depth of information collected, such as on barriers and enablers of adaptation, to better inform future interventions.

Background. Fine particulate matter (PM_2.5) is a leading global health risk. Latin American cities exhibit some of the world's highest urban PM_2.5 levels, yet studies of neighborhood-level PM_2.5 exposure and associated disparities in the region are limited. Methods. We conducted a cross-sectional ecological analysis of 53 041 neighborhoods across 340 cities in eight Latin American countries, leveraging the Salud Urbana en America Latina study dataset. Annual PM_2.5 concentrations were derived from satellite data and linked to socioeconomic and urban characteristics. A multilevel model analyzed associations between neighborhood PM_2.5 levels and neighborhood- and city-level characteristics. Results. The median annual neighborhood PM_2.5 concentration was 18.49 µg m^-3. Of the 256 million residents, all lived in neighborhoods with ambient PM_2.5 concentrations that exceeded the 2021 World Health Organization guidelines (5 µg m^-3). Variability was greatest between cities (54.3% of total variance), but substantial within-city variation (26% of variance) was observed. Higher neighborhood PM_2.5 levels were associated with higher neighborhood educational attainment (mean difference [MD] comparing top to bottom tertile = 0.17 µg m^-3), higher neighborhood intersection density (MD comparing top to bottom tertile = 0.17 µg m^-3), and older cities (MD comparing top to bottom tertile = 1.45 µg m^-3). Lower neighborhood PM_2.5 levels were related to higher neighborhood population density (MD comparing top to bottom tertile = - 0.55 µg m^-3), more greenness (MD comparing top to bottom tertile = - 0.76 µg m^-3), and larger distance from city centers (MD comparing top to bottom tertile = - 0.86 µg m^-3). Conclusions. Neighborhoods with higher PM_2.5 concentrations tended to have higher educational attainment, more intersections, and be located in older cities, while lower concentrations were associated with denser populations, more green space, and greater distance from city centers. Our findings reveal important within-city heterogeneity in PM_2.5 and the factors associated with it, suggesting strategies to mitigate air pollution within cities.

As cities in sub-Saharan Africa become more crowded, noise pollution is also emerging as an important environmental concern, after air pollution. Yet, unlike air pollution, which is enjoying relatively more public attention, there is limited measurement data and policy efforts on environmental noise pollution. We followed a recent city-wide measurement approach used in Accra (Ghana) and characterized environmental noise patterns in Kigali, a contrasting city with very different topography and regulatory system than Accra to inform urban policy. We established 10 'fixed' (yearlong) and 120 'rotating' (weeklong) monitoring sites to capture both the temporal and spatial patterns in Kigali's sound environment. The measurement occurred between November 2022 and December 2023, and samples were collected at 1 min interval, resulting in 5155 014 (3580 site-days) and 1190 620 (827 site-days) site-minutes of valid data from the fixed and rotating sites, respectively. The 130 monitoring sites covered a variety of geographic and land-use factors across diverse neighborhoods and sources. We computed several noise metrics, including 1 h (LAeq_{1 h}), daily (LAeq_{24 h}), day-time (L _day), and night-time (L _night). Daily noise (LAeq_{24 h}) levels across the city ranged between 38 dBA and 85 dBA. Commercial, business, and industrial (CBI) and high-density residential (HD) communities experienced the highest noise levels, with some sites constantly above 70 dBA at day and 65 dBA at night. About 63% of our observed day-time values (up to ~72% in some areas) exceeded the Rwandan day-time standard (55 dBA) for residential areas, whereas 69% of the observed night-time values (up to 80% in some areas) exceeded the corresponding night-time standard (45 dBA). In Nyarugenge, the most urbanized district, as much as 75% of our site-days data exceeded day-time standard. However diurnal patterns throughout the city were similar, rising from ~5 am, peaking at about 8 am and plateauing until 6 pm before falling to their lowest at midnight. Overall, noise levels in the city did not vary much by day of the week, weekdays vs weekend, or dry vs wet seasons. Environmental noise in Kigali often exceeded both Rwandan standards and international guidelines, with residents in the city center district, CBI and HD areas at risk of higher exposure, and hence higher risk of adverse effects. Detailed assessment of the sources, at-risk population, and associated health effects may inform Rwandan's environmental policy efforts and city initiatives in the face of the ongoing urban growth and densification.

Heat-health warning systems and action plans, referred to as heat prevention plans (HPPs), are key public health interventions aimed at reducing heat-related mortality. Despite their importance, prior assessments of their effectiveness have yielded inconsistent results. The objective of this study is to systematically assess the effectiveness of HPPs in reducing heat-related mortality risk across Europe. We analysed daily mortality and mean temperature data from 102 locations in 14 European countries between 1990 and 2019. Using data from national experts, we identified the year of HPP implementation and categorised their development class. A three-stage analysis was conducted: (1) quasi-Poisson time series models were used to estimate location-specific warm-season exposure-response functions in 3 year subperiods; (2) mixed-effect meta-regression models with multilevel longitudinal structures were employed to quantify changes in pooled exposure-response functions due to HPP implementation, adjusted for long-term trends in heat-related mortality risks; and (3) the heat-related excess mortality due to HPP was calculated by comparing factual (with HPP) and counterfactual (without HPP) scenarios. Estimates are reported by country, region, and HPP class. HPP implementation was associated with a 25.2% [95% CI: 19.8% to 31.9%] reduction in excess deaths attributable to extreme heat, corresponding to 1.8 [95% CI: 1.3-2.4] avoided deaths annually per 100 000 inhabitants. This equates to an estimated 14 551 [95% CI: 10 118-19 072] total deaths avoided across all study locations following HPP implementation. No significant differences in HPP effectiveness were observed by European region or HPP class. Our findings provide robust evidence that HPPs substantially reduce heat-related mortality across Europe, accounting for temporal changes and geographical differences in risks. These results emphasise the importance of monitoring and evaluating HPPs to enhance adaptation to a warming climate.

As global temperatures rise due to climate change, urban heat islands have emerged as an important public health concern, significantly exacerbating heat stress in urban populations. Meteorological data is critical for assessing heat stress, and localized microclimate data provide more precise measurements of heat hazards than traditional weather station data. Our study explored microclimate patterns in space and time in tropical cities with rapidly growing urban populations and warming climates. We established a microclimate monitoring network with sensors measuring air temperature and relative humidity throughout two large cities in Gujarat, India. We collected hourly microclimate data on temperature and humidity from April 2023 to May 2024 from paired indoor/outdoor sensors at 48 homes in Ahmedabad and 45 homes in Surat. We summarized dry bulb (T) and wet-bulb (T _w) temperatures at indoor and outdoor locations, compared temporal patterns across seasons and times of the day, and investigated relationships with urban land cover. Indoor and outdoor microclimates had different diurnal variations, with distinctive patterns during the monsoon compared to other seasons. Building volume had warming effects and vegetation had cooling effects on minimum T and T _w, particularly at outdoor locations. In contrast, building volume had cooling effects and vegetation had warming effects on maximum T and T _w, particularly at indoor locations. Temperatures were consistently cooler at locations with higher albedo, and relationships with water were weaker and more variable. A model comparison found significant differences in land cover effects for indoor versus outdoor locations. Given the increasing occurrence of heat waves and climate-related health threats in western India and other tropical areas, it will be essential to account for the different spatial and temporal patterns of indoor and outdoor microclimates to more precisely identify locations and timings of temperature extremes.

Fossil fuel energy infrastructure poses health risks for local communities, primarily due to the presence of air pollution emissions and other hazards. There is also evidence of racial/ethnic disparities in the siting of this infrastructure for select components. However, population counts and demographic composition near fossil fuel energy infrastructure have not been systematically characterized across all types, supply chain stages, and predominant fuel types. Here, we construct a dataset of 25 elements of fossil fuel energy infrastructure and characterize the populations living near this infrastructure (defined as within 800 m [∼0.5 mile] or 1.6 km [∼1 mile]). We estimated that 46.6 million people in the contiguous U.S., representing 14.1% of the population, live within 1.6 km of at least one piece of energy infrastructure, with racial/ethnic disparities observed across nearly all stages of the supply chain. End use infrastructure has the most people residing within 1.6 km, with 20.9 million people, followed by extraction (20.3 million), and storage (6.16 million). Storage infrastructure has an average of ∼2,900 people living within 1.6 km of each element; end use infrastructure has an average of 1,900 people residing within 1.6 km of each element; extraction infrastructure has an average of 17 people residing within 1.6 km of each element. Almost 90% of the population near end use, transportation, refining, and storage infrastructure are in urban areas. Our results represent a substantial population in the U.S. that is potentially exposed to hazards that are not well-characterized, with unknown cumulative impacts, and which constitute a major environmental justice issue.

Between June 6 and 8, 2023, wildfires in Quebec, Canada generated massive smoke plumes that traveled long distances and deteriorated air quality across the Northeastern United States (US). Surface daily PM_2.5 observations exceeded 100 µg m^-3, affecting major cities such as New York City and Philadelphia, while many areas lacked PM_2.5 monitors, making it difficult to assess local air quality conditions. To address this gap, we developed a WRF-CMAQ-BenMAP modeling system to provide rapid, spatially continuous estimates of wildfire-attributable PM_2.5 concentrations and associated health impacts, particularly benefiting regions lacking air quality monitoring. CMAQ simulations driven by two wildfire emissions datasets and two meteorological drivers showed good agreement with PM_2.5 observations, with linear regression results of R² ∼0.6 and slope ∼0.9. We further quantified uncertainties introduced by varying emissions and meteorological drivers and found the choice of wildfire emissions dataset alone can alter PM_2.5 simulations by up to 40 µg m^-3 (∼40%). Short-term health impacts were evaluated using the BenMAP model. Validation against asthma-associated emergency department (ED) visits in New York State confirmed the framework's ability to replicate real-world outcomes, with ED visits increased up to ∼40%. The modeling results identified counties most severely affected by wildfire plumes, the majority of which lack regulatory air quality monitors. Our approach highlights the value of integrated modeling for identifying vulnerable populations and delivering timely health burden estimates, regardless of local monitoring availability.

The effects of a changing climate are already evident in Caribbean small island developing states (SIDS) like Puerto Rico, where heat episodes have become more frequent. Despite reports of increasing heat-related death rates, robust epidemiological evidence on the health impacts of high temperatures, as well as the effects of low temperatures, remains scarce, particularly outside of urban settlements in Caribbean SIDS. In this study, we conducted a case time-series study on municipality-level mortality and temperature in Puerto Rico from 2015-2023. We modeled the relationship between daily mortality count and mean temperature using a conditional quasi-Poisson regression, combined with a distributed lag non-linear model (dlnm) with a 21 d lag, adjusting for relative humidity, seasonality, and day of the week. We estimated the minimum mortality temperature (MMT)-the optimal temperature associated with the lowest mortality risk-and calculated the relative risk associated with extreme low and high temperature, defined as the 2.5th and 97.5th percentiles of daily temperature. Additionally, we estimated the municipality- and island-level excess mortality fractions attributable to both low and high temperatures, relative to MMT. Our findings indicate that exposure to non-optimum temperatures (both low and high temperatures) is significantly associated with increased mortality risk. Specifically, extreme low temperature was associated with a 1.23 (95% CI: 1.07-1.40) times risk of all-cause mortality, while extreme high temperature was associated with a 1.16 (95% CI: 1.05-1.27) times risk. We estimated that temperature-related mortality accounted for 3.88% of the total 280 568 deaths (95% eCI: 3.39%-4.29%), with low temperatures contributing 2.02% (95% eCI: 1.69%-2.32%) and high temperatures contributing 1.86% (95% eCI: 1.35%-2.35%). Furthermore, we found substantial spatial variability in temperature-related mortality burdens across municipalities. Our study identifies the vulnerable municipalities to temperature-related deaths in Puerto Rico, providing evidence to inform municipality-specific climate adaptation and mitigation strategies.